diff --git a/README.md b/README.md
index c974c186..12bbd71d 100644
--- a/README.md
+++ b/README.md
@@ -81,10 +81,15 @@ Note that this started just as a [fun weekend project](https://localai.io/#backs
 
 ## 🔥🔥 Hot topics / Roadmap
 
-- [Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
+[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
 
-Hot topics:
-- https://github.com/mudler/LocalAI/issues/1126
+🆕 New! [LLM finetuning guide](https://localai.io/advanced/fine-tuning/)
+
+Hot topics (looking for contributors):
+- Backends v2: https://github.com/mudler/LocalAI/issues/1126
+- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
+
+If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
 
 ## 🚀 [Features](https://localai.io/features/)
 
@@ -98,20 +103,13 @@ Hot topics:
 - 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
 - 🆕 [Vision API](https://localai.io/features/gpt-vision/)
 
-## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
-
-- [Create a slackbot for teams and OSS projects that answer to documentation](https://mudler.pm/posts/smart-slackbot-for-teams/)
-- [LocalAI meets k8sgpt](https://www.youtube.com/watch?v=PKrDNuJ_dfE)
-- [Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All](https://mudler.pm/posts/localai-question-answering/)
-- [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65)
-
 ## 💻 Usage
 
 Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
 
-### Community
+### 🔗 Community and integrations
 
-WebUI
+WebUIs:
 - https://github.com/Jirubizu/localai-admin
 - https://github.com/go-skynet/LocalAI-frontend
 
@@ -123,11 +121,19 @@ Other:
 
 ### 🔗 Resources
 
+- 🆕 New! [LLM finetuning guide](https://localai.io/advanced/fine-tuning/)
 - [How to build locally](https://localai.io/basics/build/index.html)
 - [How to install in Kubernetes](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes)
 - [Projects integrating LocalAI](https://localai.io/integrations/)
 - [How tos section](https://localai.io/howtos/) (curated by our community)
   
+## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
+
+- [Create a slackbot for teams and OSS projects that answer to documentation](https://mudler.pm/posts/smart-slackbot-for-teams/)
+- [LocalAI meets k8sgpt](https://www.youtube.com/watch?v=PKrDNuJ_dfE)
+- [Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All](https://mudler.pm/posts/localai-question-answering/)
+- [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65)
+
 ## Citation
 
 If you utilize this repository, data in a downstream project, please consider citing it with:
diff --git a/docs/content/_index.en.md b/docs/content/_index.en.md
index 121e4782..de8d7496 100644
--- a/docs/content/_index.en.md
+++ b/docs/content/_index.en.md
@@ -89,10 +89,15 @@ Note that this started just as a [fun weekend project](https://localai.io/#backs
 
 ## 🔥🔥 Hot topics / Roadmap
 
-- [Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
+[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
 
-Hot topics:
-- https://github.com/mudler/LocalAI/issues/1126
+🆕 New! [LLM finetuning guide](https://localai.io/advanced/fine-tuning/)
+
+Hot topics (looking for contributors):
+- Backends v2: https://github.com/mudler/LocalAI/issues/1126
+- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
+
+If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
 
 ## How does it work?
 
diff --git a/docs/content/advanced/fine-tuning.md b/docs/content/advanced/fine-tuning.md
new file mode 100644
index 00000000..7cf14161
--- /dev/null
+++ b/docs/content/advanced/fine-tuning.md
@@ -0,0 +1,134 @@
+
++++
+disableToc = false
+title = "Fine-tuning LLMs for text generation"
+weight = 3
++++
+
+{{% notice note %}}
+Section under construction
+{{% /notice %}}
+
+This section covers how to fine-tune a language model for text generation and consume it in LocalAI.
+
+## Requirements
+
+For this example you will need at least a 12GB VRAM of GPU and a Linux box.
+
+## Fine-tuning
+
+Fine-tuning a language model is a process that requires a lot of computational power and time.
+
+Currently LocalAI doesn't support the fine-tuning endpoint as LocalAI but there are are [plans](https://github.com/mudler/LocalAI/issues/596) to support that. For the time being a guide is proposed here to give a simple starting point on how to fine-tune a model and use it with LocalAI (but also with llama.cpp).
+
+There is an e2e example of fine-tuning a LLM model to use with [LocalAI](https://github/mudler/LocalAI) written by [@mudler](https://github.com/mudler) available [here](https://github.com/mudler/LocalAI/tree/master/examples/e2e-fine-tuning/).
+
+The steps involved are:
+
+- Preparing a dataset
+- Prepare the environment and install dependencies
+- Fine-tune the model
+- Merge the Lora base with the model
+- Convert the model to gguf
+- Use the model with LocalAI
+
+## Dataset preparation
+
+We are going to need a dataset or a set of datasets. 
+
+Axolotl supports a variety of formats, in the notebook and in this example we are aiming for a very simple dataset and build that manually, so we are going to use the `completion` format which requires the full text to be used for fine-tuning.
+
+A dataset for an instructor model (like Alpaca) can look like the following:
+
+```json
+[
+ {
+    "text": "As an AI language model you are trained to reply to an instruction. Try to be as much polite as possible\n\n## Instruction\n\nWrite a poem about a tree.\n\n## Response\n\nTrees are beautiful, ...",
+ },
+ {
+    "text": "As an AI language model you are trained to reply to an instruction. Try to be as much polite as possible\n\n## Instruction\n\nWrite a poem about a tree.\n\n## Response\n\nTrees are beautiful, ...",
+ }
+]
+```
+
+Every block in the text is the whole text that is used to fine-tune. For example, for an instructor model it follows the following format (more or less):
+
+```
+<System prompt>
+
+## Instruction
+
+<Question, instruction>
+
+## Response
+
+<Expected response from the LLM>
+```
+
+The instruction format works such as when we are going to inference with the model, we are going to feed it only the first part up to the `## Instruction` block, and the model is going to complete the text with the `## Response` block.
+
+Prepare a dataset, and upload it to your Google Drive in case you are using the Google colab. Otherwise place it next the `axolotl.yaml` file as `dataset.json`.
+
+### Install dependencies
+
+```bash
+# Install axolotl and dependencies
+git clone https://github.com/OpenAccess-AI-Collective/axolotl && pushd axolotl && git checkout 797f3dd1de8fd8c0eafbd1c9fdb172abd9ff840a && popd #0.3.0
+pip install packaging
+pushd axolotl && pip install -e '.[flash-attn,deepspeed]' && popd
+
+# https://github.com/oobabooga/text-generation-webui/issues/4238
+pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.0/flash_attn-2.3.0+cu117torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
+```
+
+Configure accelerate:
+
+```bash
+accelerate config default
+```
+
+## Fine-tuning
+
+We will need to configure axolotl. In this example is provided a file to use `axolotl.yaml` that uses openllama-3b for fine-tuning. Copy the `axolotl.yaml` file and edit it to your needs. The dataset needs to be next to it as `dataset.json`. You can find the axolotl.yaml file [here](https://github.com/mudler/LocalAI/tree/master/examples/e2e-fine-tuning/).
+
+If you have a big dataset, you can pre-tokenize it to speedup the fine-tuning process:
+
+```bash
+# Optional pre-tokenize (run only if big dataset)
+python -m axolotl.cli.preprocess axolotl.yaml
+```
+
+Now we are ready to start the fine-tuning process:
+```bash
+# Fine-tune
+accelerate launch -m axolotl.cli.train axolotl.yaml
+```
+
+After we have finished the fine-tuning, we merge the Lora base with the model:
+```bash
+# Merge lora
+python3 -m axolotl.cli.merge_lora axolotl.yaml --lora_model_dir="./qlora-out" --load_in_8bit=False --load_in_4bit=False
+```
+
+And we convert it to the gguf format that LocalAI can consume:
+
+```bash
+
+# Convert to gguf
+git clone https://github.com/ggerganov/llama.cpp.git
+pushd llama.cpp && make LLAMA_CUBLAS=1 && popd
+
+# We need to convert the pytorch model into ggml for quantization
+# It crates 'ggml-model-f16.bin' in the 'merged' directory.
+pushd llama.cpp && python convert.py --outtype f16 \
+    ../qlora-out/merged/pytorch_model-00001-of-00002.bin && popd
+
+# Start off by making a basic q4_0 4-bit quantization.
+# It's important to have 'ggml' in the name of the quant for some
+# software to recognize it's file format.
+pushd llama.cpp &&  ./quantize ../qlora-out/merged/ggml-model-f16.gguf \
+    ../custom-model-q4_0.bin q4_0
+
+```
+
+Now you should have ended up with a `custom-model-q4_0.bin` file that you can copy in the LocalAI models directory and use it with LocalAI.
diff --git a/examples/README.md b/examples/README.md
index 7f6dccb9..debfe1a5 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -41,6 +41,14 @@ This example show how to use LocalAI inside Kubernetes with [k8sgpt](https://k8s
 
 ![Screenshot from 2023-06-19 23-58-47](https://github.com/go-skynet/go-ggml-transformers.cpp/assets/2420543/cab87409-ee68-44ae-8d53-41627fb49509)
 
+### Fine-tuning a model and convert it to gguf to use it with LocalAI
+
+_by [@mudler](https://github.com/mudler)_
+
+This example is an e2e example on how to fine-tune a model with [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) and convert it to gguf to use it with LocalAI.
+
+[Check it out here](https://github.com/mudler/LocalAI/tree/master/examples/e2e-fine-tuning/)
+
 ### Flowise
 
 _by [@mudler](https://github.com/mudler)_
diff --git a/examples/e2e-fine-tuning/README.md b/examples/e2e-fine-tuning/README.md
new file mode 100644
index 00000000..a9258c01
--- /dev/null
+++ b/examples/e2e-fine-tuning/README.md
@@ -0,0 +1,83 @@
+This is an example of fine-tuning a LLM model to use with [LocalAI](https://github/mudler/LocalAI) written by [@mudler](https://github.com/mudler).
+
+Specifically, this example shows how to use [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) to fine-tune a LLM model to consume with LocalAI as a `gguf` model.
+
+A notebook is provided that currently works on _very small_ datasets on Google colab on the free instance. It is far from producing good models, but it gives a sense of how to use the code to use with a better dataset and configurations, and how to use the model produced with LocalAI.
+
+## Requirements
+
+For this example you will need at least a 12GB VRAM of GPU and a Linux box.
+The notebook is tested on Google Colab with a Tesla T4 GPU.
+
+## Clone this directory
+
+Clone the repository and enter the example directory:
+
+```bash
+git clone http://github.com/mudler/LocalAI
+cd LocalAI/examples/e2e-fine-tuning
+```
+
+## Install dependencies
+
+```bash
+# Install axolotl and dependencies
+git clone https://github.com/OpenAccess-AI-Collective/axolotl && pushd axolotl && git checkout 797f3dd1de8fd8c0eafbd1c9fdb172abd9ff840a && popd #0.3.0
+pip install packaging
+pushd axolotl && pip install -e '.[flash-attn,deepspeed]' && popd
+
+# https://github.com/oobabooga/text-generation-webui/issues/4238
+pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.0/flash_attn-2.3.0+cu117torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
+```
+
+Configure accelerate:
+
+```bash
+accelerate config default
+```
+
+## Fine-tuning
+
+We will need to configure axolotl. In this example is provided a file to use `axolotl.yaml` that uses openllama-3b for fine-tuning. Copy the `axolotl.yaml` file and edit it to your needs. The dataset needs to be next to it as `dataset.json`. The format used is `completion` which is a list of JSON objects with a `text` field with the full text to train the LLM with.
+
+If you have a big dataset, you can pre-tokenize it to speedup the fine-tuning process:
+
+```bash
+# Optional pre-tokenize (run only if big dataset)
+python -m axolotl.cli.preprocess axolotl.yaml
+```
+
+Now we are ready to start the fine-tuning process:
+```bash
+# Fine-tune
+accelerate launch -m axolotl.cli.train axolotl.yaml
+```
+
+After we have finished the fine-tuning, we merge the Lora base with the model:
+```bash
+# Merge lora
+python3 -m axolotl.cli.merge_lora axolotl.yaml --lora_model_dir="./qlora-out" --load_in_8bit=False --load_in_4bit=False
+```
+
+And we convert it to the gguf format that LocalAI can consume:
+
+```bash
+
+# Convert to gguf
+git clone https://github.com/ggerganov/llama.cpp.git
+pushd llama.cpp && make LLAMA_CUBLAS=1 && popd
+
+# We need to convert the pytorch model into ggml for quantization
+# It crates 'ggml-model-f16.bin' in the 'merged' directory.
+pushd llama.cpp && python convert.py --outtype f16 \
+    ../qlora-out/merged/pytorch_model-00001-of-00002.bin && popd
+
+# Start off by making a basic q4_0 4-bit quantization.
+# It's important to have 'ggml' in the name of the quant for some
+# software to recognize it's file format.
+pushd llama.cpp &&  ./quantize ../qlora-out/merged/ggml-model-f16.gguf \
+    ../custom-model-q4_0.bin q4_0
+
+```
+
+Now you should have ended up with a `custom-model-q4_0.bin` file that you can copy in the LocalAI models directory and use it with LocalAI.
diff --git a/examples/e2e-fine-tuning/axolotl.yaml b/examples/e2e-fine-tuning/axolotl.yaml
new file mode 100644
index 00000000..ea956dd4
--- /dev/null
+++ b/examples/e2e-fine-tuning/axolotl.yaml
@@ -0,0 +1,63 @@
+
+base_model: openlm-research/open_llama_3b_v2
+model_type: LlamaForCausalLM
+tokenizer_type: LlamaTokenizer
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+push_dataset_to_hub: false
+datasets:
+- path: dataset.json
+  ds_type: json
+  type: completion
+dataset_prepared_path:
+val_set_size: 0.05
+adapter: qlora
+lora_model_dir:
+sequence_len: 1024
+sample_packing: true
+lora_r: 8
+lora_alpha: 32
+lora_dropout: 0.05
+lora_target_modules:
+lora_target_linear: true
+lora_fan_in_fan_out:
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+output_dir: ./qlora-out
+gradient_accumulation_steps: 1
+micro_batch_size: 2
+num_epochs: 4
+optimizer: paged_adamw_32bit
+torchdistx_path:
+lr_scheduler: cosine
+learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
+bf16: false
+fp16: true
+tf32: false
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: false
+gptq_groupsize:
+gptq_model_v1:
+warmup_steps: 20
+eval_steps: 0.05
+save_steps:
+debug:
+deepspeed:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+bos_token: "<s>"
+eos_token: "</s>"
+unk_token: "<unk>"
diff --git a/examples/e2e-fine-tuning/notebook.ipynb b/examples/e2e-fine-tuning/notebook.ipynb
new file mode 100644
index 00000000..9efb57d2
--- /dev/null
+++ b/examples/e2e-fine-tuning/notebook.ipynb
@@ -0,0 +1,1655 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Finetuning a model and using it with LocalAI\n",
+        "\n",
+        "This is an example of fine-tuning a LLM model to use with [LocalAI](https://github/mudler/LocalAI) written by [@mudler](https://github.com/mudler).\n",
+        "\n",
+        "Specifically, this example shows how to use [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) to fine-tune a LLM model to consume with LocalAI as a `gguf` model."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "puRhZeHvuHgB"
+      },
+      "source": [
+        "# Important!\n",
+        "\n",
+        "Before starting, make sure you have selected GPU runtime : Runtime -> Change runtime type -> GPU (T4)!"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "xcUAOoASZUV1"
+      },
+      "source": [
+        "Change the model to link to your dataset. Upload the dataset as `output.jsonl` in the root tree and edit the model file (model.yml) with:\n",
+        "\n",
+        "```\n",
+        "# local\n",
+        "datasets:\n",
+        "  - path: /content/output.jsonl\n",
+        "    ds_type: json\n",
+        "    type: completion\n",
+        "\n",
+        "```\n",
+        "\n",
+        "A full example:\n",
+        "\n",
+        "```yaml\n",
+        "\n",
+        "base_model: openlm-research/open_llama_3b_v2\n",
+        "model_type: LlamaForCausalLM\n",
+        "tokenizer_type: LlamaTokenizer\n",
+        "load_in_8bit: false\n",
+        "load_in_4bit: true\n",
+        "strict: false\n",
+        "push_dataset_to_hub: false\n",
+        "datasets:\n",
+        "  - path: /content/output.jsonl\n",
+        "    ds_type: json\n",
+        "    type: completion\n",
+        "dataset_prepared_path:\n",
+        "val_set_size: 0.05\n",
+        "adapter: qlora\n",
+        "lora_model_dir:\n",
+        "sequence_len: 1024\n",
+        "sample_packing: true\n",
+        "lora_r: 8\n",
+        "lora_alpha: 32\n",
+        "lora_dropout: 0.05\n",
+        "lora_target_modules:\n",
+        "lora_target_linear: true\n",
+        "lora_fan_in_fan_out:\n",
+        "wandb_project:\n",
+        "wandb_entity:\n",
+        "wandb_watch:\n",
+        "wandb_run_id:\n",
+        "wandb_log_model:\n",
+        "output_dir: ./qlora-out\n",
+        "gradient_accumulation_steps: 1\n",
+        "micro_batch_size: 2\n",
+        "num_epochs: 4\n",
+        "optimizer: paged_adamw_32bit\n",
+        "torchdistx_path:\n",
+        "lr_scheduler: cosine\n",
+        "learning_rate: 0.0002\n",
+        "train_on_inputs: false\n",
+        "group_by_length: false\n",
+        "bf16: false\n",
+        "fp16: true\n",
+        "tf32: false\n",
+        "gradient_checkpointing: true\n",
+        "early_stopping_patience:\n",
+        "resume_from_checkpoint:\n",
+        "local_rank:\n",
+        "logging_steps: 1\n",
+        "xformers_attention:\n",
+        "flash_attention: false\n",
+        "gptq_groupsize:\n",
+        "gptq_model_v1:\n",
+        "warmup_steps: 20\n",
+        "eval_steps: 0.05\n",
+        "save_steps:\n",
+        "debug:\n",
+        "deepspeed:\n",
+        "weight_decay: 0.1\n",
+        "fsdp:\n",
+        "fsdp_config:\n",
+        "special_tokens:\n",
+        "  bos_token: \"<s>\"\n",
+        "  eos_token: \"</s>\"\n",
+        "  unk_token: \"<unk>\"\n",
+        "\n",
+        "```"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "CBVQikr2WiFP",
+        "outputId": "236f9f0e-b2b5-4ba9-9127-27f804c511db"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Cloning into 'axolotl'...\n",
+            "remote: Enumerating objects: 7525, done.\u001b[K\n",
+            "remote: Counting objects: 100% (1726/1726), done.\u001b[K\n",
+            "remote: Compressing objects: 100% (385/385), done.\u001b[K\n",
+            "remote: Total 7525 (delta 1525), reused 1409 (delta 1319), pack-reused 5799\u001b[K\n",
+            "Receiving objects: 100% (7525/7525), 2.64 MiB | 10.52 MiB/s, done.\n",
+            "Resolving deltas: 100% (4854/4854), done.\n",
+            "Note: switching to '797f3dd1de8fd8c0eafbd1c9fdb172abd9ff840a'.\n",
+            "\n",
+            "You are in 'detached HEAD' state. You can look around, make experimental\n",
+            "changes and commit them, and you can discard any commits you make in this\n",
+            "state without impacting any branches by switching back to a branch.\n",
+            "\n",
+            "If you want to create a new branch to retain commits you create, you may\n",
+            "do so (now or later) by using -c with the switch command. Example:\n",
+            "\n",
+            "  git switch -c <new-branch-name>\n",
+            "\n",
+            "Or undo this operation with:\n",
+            "\n",
+            "  git switch -\n",
+            "\n",
+            "Turn off this advice by setting config variable advice.detachedHead to false\n",
+            "\n",
+            "HEAD is now at 797f3dd don't train if eval split is too small (#873)\n",
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+            "Collecting auto-gptq==0.5.1 (from axolotl==0.3.0)\n",
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+            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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+            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
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+            "\u001b[?25hINFO: pip is looking at multiple versions of s3fs to determine which version is compatible with other requirements. This could take a while.\n",
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+            "INFO: pip is looking at multiple versions of tokenizers to determine which version is compatible with other requirements. This could take a while.\n",
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+            "  Downloading tokenizers-0.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.8 MB)\n",
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+            "\u001b[?25hCollecting gradio-client==0.6.0 (from gradio->axolotl==0.3.0)\n",
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+            "\u001b[?25hINFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
+            "  Downloading gradio-3.46.1-py3-none-any.whl (20.2 MB)\n",
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+            "\u001b[?25hCollecting gradio-client==0.5.3 (from gradio->axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting gradio (from axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting gradio-client==0.5.2 (from gradio->axolotl==0.3.0)\n",
+            "  Downloading gradio_client-0.5.2-py3-none-any.whl (298 kB)\n",
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+            "\u001b[?25hCollecting gradio (from axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting gradio (from axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting gradio-client==0.1.2 (from gradio->axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting pycryptodome (from gradio->axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting datasets>=2.14.0 (from axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting huggingface-hub (from accelerate==0.24.1->axolotl==0.3.0)\n",
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+            "\u001b[?25hINFO: pip is looking at multiple versions of s3fs to determine which version is compatible with other requirements. This could take a while.\n",
+            "INFO: pip is looking at multiple versions of transformers[sentencepiece] to determine which version is compatible with other requirements. This could take a while.\n",
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+            "Collecting starlette<0.28.0,>=0.27.0 (from fastapi->fschat==0.2.29->axolotl==0.3.0)\n",
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+            "\u001b[?25hCollecting typing-extensions (from torch>=1.10.0->accelerate==0.24.1->axolotl==0.3.0)\n",
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+            "  Downloading wavedrom-2.0.3.post3.tar.gz (137 kB)\n",
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+            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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+            "Collecting jmespath<2.0.0,>=0.7.1 (from botocore<1.31.18,>=1.31.17->aiobotocore~=2.5.4->s3fs->axolotl==0.3.0)\n",
+            "  Downloading jmespath-1.0.1-py3-none-any.whl (20 kB)\n",
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+            "\u001b[?25hCollecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb->axolotl==0.3.0)\n",
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+            "Collecting svgwrite (from wavedrom->markdown2[all]->fschat==0.2.29->axolotl==0.3.0)\n",
+            "  Downloading svgwrite-1.4.3-py3-none-any.whl (67 kB)\n",
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+            "\u001b[?25hBuilding wheels for collected packages: optimum, rouge-score, flash-attn, deepspeed, fire, ffmpy, wavedrom, lit\n",
+            "  Building wheel for optimum (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for optimum: filename=optimum-1.13.2-py3-none-any.whl size=395598 sha256=c50241754999443c85c875c140c77aa5bf3a40f56a5ffd196d1f3c5199609431\n",
+            "  Stored in directory: /root/.cache/pip/wheels/6e/b7/2c/79405d98f0943373d8546daeae25a3d377f7659ca0cbe48699\n",
+            "  Building wheel for rouge-score (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for rouge-score: filename=rouge_score-0.1.2-py3-none-any.whl size=24933 sha256=cc9084a7eefdb136724effd732f6cb7c0fd01f0d7c9e7852043f1cd1d23b45a9\n",
+            "  Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4\n",
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+            "  Created wheel for flash-attn: filename=flash_attn-2.3.3-cp310-cp310-linux_x86_64.whl size=57075008 sha256=bcb63b64213ab61590b340b77de84e448a442e19c100480895194df39ad7673d\n",
+            "  Stored in directory: /root/.cache/pip/wheels/e5/e6/fa/941802ec61d1afd320d27160ab1db98e6dba65381f84b76d4a\n",
+            "  Building wheel for deepspeed (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for deepspeed: filename=deepspeed-0.12.3-py3-none-any.whl size=1279165 sha256=e678c7b56fa15c9218f88c9a8a48728bee271215c554abcb4049f609e47adb25\n",
+            "  Stored in directory: /root/.cache/pip/wheels/ee/2b/c5/892ceee06964ce8aa2a98d4260848d0d9a3f1e743862e4b45a\n",
+            "  Building wheel for fire (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for fire: filename=fire-0.5.0-py2.py3-none-any.whl size=116933 sha256=2e829d74a791417c18e5d80016d0125dc65481ae4577bfd4041e51aa64558256\n",
+            "  Stored in directory: /root/.cache/pip/wheels/90/d4/f7/9404e5db0116bd4d43e5666eaa3e70ab53723e1e3ea40c9a95\n",
+            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=dd713b1fe6d28ec101c96dbf7033241901635fcddd42a07d9e97fafada70eca4\n",
+            "  Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n",
+            "  Building wheel for wavedrom (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for wavedrom: filename=wavedrom-2.0.3.post3-py2.py3-none-any.whl size=30053 sha256=65b629500b343fc851f1c23dd2065fa414153974ae25603bba9f99e559ecbf8c\n",
+            "  Stored in directory: /root/.cache/pip/wheels/9c/52/8c/38b454b42f712f325e26f633287484c7dc1ad469e1580c5954\n",
+            "  Building wheel for lit (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for lit: filename=lit-17.0.5-py3-none-any.whl size=93256 sha256=209fa0a842c16d9479d3626694714ebd0b9f4afaaacf487e3fb92d19ecfa9fcf\n",
+            "  Stored in directory: /root/.cache/pip/wheels/1c/87/8e/5a42c0d4be23362b68bbff33b17f3c35a3df44f1cd2f5a24b4\n",
+            "Successfully built optimum rouge-score flash-attn deepspeed fire ffmpy wavedrom lit\n",
+            "Installing collected packages: sentencepiece, pydub, ninja, nh3, lit, hjson, ffmpy, bitsandbytes, addict, websockets, urllib3, typing-extensions, svgwrite, smmap, shortuuid, setproctitle, semantic-version, rouge, python-multipart, pynvml, pyarrow-hotfix, orjson, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, numpy, markdown2, jmespath, humanfriendly, hf_transfer, h11, fire, einops, docker-pycreds, dill, colorama, art, aioitertools, aiofiles, wavedrom, uvicorn, starlette, sentry-sdk, rouge-score, nvidia-cusolver-cu11, nvidia-cudnn-cu11, multiprocess, httpcore, gitdb, gekko, coloredlogs, botocore, tiktoken, responses, huggingface-hub, httpx, GitPython, fastapi, aiobotocore, wandb, tokenizers, s3fs, gradio-client, fschat, datasets, transformers, gradio, evaluate, triton, torch, accelerate, peft, xformers, optimum, bert-score, auto-gptq, flash-attn, deepspeed, axolotl\n",
+            "  Attempting uninstall: urllib3\n",
+            "    Found existing installation: urllib3 2.0.7\n",
+            "    Uninstalling urllib3-2.0.7:\n",
+            "      Successfully uninstalled urllib3-2.0.7\n",
+            "  Attempting uninstall: typing-extensions\n",
+            "    Found existing installation: typing_extensions 4.5.0\n",
+            "    Uninstalling typing_extensions-4.5.0:\n",
+            "      Successfully uninstalled typing_extensions-4.5.0\n",
+            "  Attempting uninstall: numpy\n",
+            "    Found existing installation: numpy 1.23.5\n",
+            "    Uninstalling numpy-1.23.5:\n",
+            "      Successfully uninstalled numpy-1.23.5\n",
+            "  Attempting uninstall: huggingface-hub\n",
+            "    Found existing installation: huggingface-hub 0.19.3\n",
+            "    Uninstalling huggingface-hub-0.19.3:\n",
+            "      Successfully uninstalled huggingface-hub-0.19.3\n",
+            "  Attempting uninstall: tokenizers\n",
+            "    Found existing installation: tokenizers 0.15.0\n",
+            "    Uninstalling tokenizers-0.15.0:\n",
+            "      Successfully uninstalled tokenizers-0.15.0\n",
+            "  Attempting uninstall: transformers\n",
+            "    Found existing installation: transformers 4.35.2\n",
+            "    Uninstalling transformers-4.35.2:\n",
+            "      Successfully uninstalled transformers-4.35.2\n",
+            "  Attempting uninstall: triton\n",
+            "    Found existing installation: triton 2.1.0\n",
+            "    Uninstalling triton-2.1.0:\n",
+            "      Successfully uninstalled triton-2.1.0\n",
+            "  Attempting uninstall: torch\n",
+            "    Found existing installation: torch 2.1.0+cu118\n",
+            "    Uninstalling torch-2.1.0+cu118:\n",
+            "      Successfully uninstalled torch-2.1.0+cu118\n",
+            "  Running setup.py develop for axolotl\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "lida 0.0.10 requires kaleido, which is not installed.\n",
+            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
+            "llmx 0.0.15a0 requires openai, which is not installed.\n",
+            "cupy-cuda11x 11.0.0 requires numpy<1.26,>=1.20, but you have numpy 1.26.2 which is incompatible.\n",
+            "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\n",
+            "torchaudio 2.1.0+cu118 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n",
+            "torchdata 0.7.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n",
+            "torchtext 0.16.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n",
+            "torchvision 0.16.0+cu118 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed GitPython-3.1.40 accelerate-0.24.1 addict-2.4.0 aiobotocore-2.5.4 aiofiles-23.2.1 aioitertools-0.11.0 art-6.1 auto-gptq-0.5.1 axolotl-0.3.0 bert-score-0.3.13 bitsandbytes-0.41.2.post2 botocore-1.31.17 colorama-0.4.6 coloredlogs-15.0.1 datasets-2.14.7 deepspeed-0.12.3 dill-0.3.7 docker-pycreds-0.4.0 einops-0.7.0 evaluate-0.4.0 fastapi-0.104.1 ffmpy-0.3.1 fire-0.5.0 flash-attn-2.3.3 fschat-0.2.29 gekko-1.0.6 gitdb-4.0.11 gradio-3.50.2 gradio-client-0.6.1 h11-0.14.0 hf_transfer-0.1.4 hjson-3.1.0 httpcore-1.0.2 httpx-0.25.1 huggingface-hub-0.17.3 humanfriendly-10.0 jmespath-1.0.1 lit-17.0.5 markdown2-2.4.10 multiprocess-0.70.15 nh3-0.2.14 ninja-1.11.1.1 numpy-1.26.2 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 optimum-1.13.2 orjson-3.9.10 peft-0.6.0 pyarrow-hotfix-0.5 pydub-0.25.1 pynvml-11.5.0 python-multipart-0.0.6 responses-0.18.0 rouge-1.0.1 rouge-score-0.1.2 s3fs-2023.6.0 semantic-version-2.10.0 sentencepiece-0.1.99 sentry-sdk-1.35.0 setproctitle-1.3.3 shortuuid-1.0.11 smmap-5.0.1 starlette-0.27.0 svgwrite-1.4.3 tiktoken-0.5.1 tokenizers-0.14.1 torch-2.0.1 transformers-4.35.1 triton-2.0.0 typing-extensions-4.8.0 urllib3-1.26.18 uvicorn-0.24.0.post1 wandb-0.16.0 wavedrom-2.0.3.post3 websockets-11.0.3 xformers-0.0.22\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Install axolotl\n",
+        "!git clone https://github.com/OpenAccess-AI-Collective/axolotl  && cd axolotl && git checkout 797f3dd1de8fd8c0eafbd1c9fdb172abd9ff840a #0.3.0\n",
+        "!cd axolotl\n",
+        "!pip install packaging\n",
+        "!cd axolotl && pip install -e '.[flash-attn,deepspeed]'"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ET82VllsW6gU",
+        "outputId": "27e4d16a-da64-46ed-b927-ce12b3f9af6d"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "accelerate configuration saved at /root/.cache/huggingface/accelerate/default_config.yaml\n"
+          ]
+        }
+      ],
+      "source": [
+        "!accelerate config default"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "n_xquNdQYsMX",
+        "outputId": "68de83a9-2e5a-49e6-ff06-5013eb085370"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (0.24.1)\n",
+            "Requirement already satisfied: bitsandbytes in /usr/local/lib/python3.10/dist-packages (0.41.2.post2)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.26.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (23.2)\n",
+            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n",
+            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate) (6.0.1)\n",
+            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (2.0.1)\n",
+            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from accelerate) (0.17.3)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.13.1)\n",
+            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (4.8.0)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.2.1)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1.2)\n",
+            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.99)\n",
+            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.99)\n",
+            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.101)\n",
+            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (8.5.0.96)\n",
+            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.10.3.66)\n",
+            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (10.9.0.58)\n",
+            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (10.2.10.91)\n",
+            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.4.0.1)\n",
+            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.4.91)\n",
+            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.14.3)\n",
+            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.91)\n",
+            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.0.0)\n",
+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10.0->accelerate) (67.7.2)\n",
+            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10.0->accelerate) (0.41.3)\n",
+            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (3.27.7)\n",
+            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (17.0.5)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (2023.6.0)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (2.31.0)\n",
+            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (4.66.1)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.3)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.4)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (1.26.18)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2023.7.22)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
+            "/content\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install accelerate bitsandbytes\n",
+        "!pwd"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IZv_VnRrtTSz",
+        "outputId": "36439ab2-c4de-46b5-dd36-b90d09db8358"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "import torch\n",
+        "torch.cuda.is_available()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "9SwNYGmisJU6",
+        "outputId": "963ffc20-dd38-48e4-f72d-8a4d78e36461"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.35.1)\n",
+            "Collecting transformers\n",
+            "  Downloading transformers-4.35.2-py3-none-any.whl (7.9 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.9/7.9 MB\u001b[0m \u001b[31m24.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.13.1)\n",
+            "Requirement already satisfied: huggingface-hub<1.0,>=0.16.4 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.17.3)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.26.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.2)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.6.3)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
+            "Requirement already satisfied: tokenizers<0.19,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.14.1)\n",
+            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.0)\n",
+            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.1)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->transformers) (2023.6.0)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->transformers) (4.8.0)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.18)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.7.22)\n",
+            "Installing collected packages: transformers\n",
+            "  Attempting uninstall: transformers\n",
+            "    Found existing installation: transformers 4.35.1\n",
+            "    Uninstalling transformers-4.35.1:\n",
+            "      Successfully uninstalled transformers-4.35.1\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "axolotl 0.3.0 requires transformers==4.35.1, but you have transformers 4.35.2 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed transformers-4.35.2\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install --upgrade transformers"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "jCsnQhmave0Z",
+        "outputId": "6c9f39ef-0e4a-41cb-ee22-8c71438e254e"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Collecting flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE\n",
+            "  Downloading https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.0/flash_attn-2.3.0+cu117torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl (30.0 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m30.0/30.0 MB\u001b[0m \u001b[31m46.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (2.0.1)\n",
+            "Requirement already satisfied: einops in /usr/local/lib/python3.10/dist-packages (from flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (0.7.0)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (23.2)\n",
+            "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (1.11.1.1)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (3.13.1)\n",
+            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (4.8.0)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (3.2.1)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (3.1.2)\n",
+            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.7.99)\n",
+            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.7.99)\n",
+            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.7.101)\n",
+            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (8.5.0.96)\n",
+            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.10.3.66)\n",
+            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (10.9.0.58)\n",
+            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (10.2.10.91)\n",
+            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.4.0.1)\n",
+            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.7.4.91)\n",
+            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (2.14.3)\n",
+            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (11.7.91)\n",
+            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (2.0.0)\n",
+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (67.7.2)\n",
+            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (0.41.3)\n",
+            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (3.27.7)\n",
+            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (17.0.5)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (2.1.3)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (1.3.0)\n",
+            "Installing collected packages: flash-attn\n",
+            "  Attempting uninstall: flash-attn\n",
+            "    Found existing installation: flash-attn 2.3.3\n",
+            "    Uninstalling flash-attn-2.3.3:\n",
+            "      Successfully uninstalled flash-attn-2.3.3\n",
+            "Successfully installed flash-attn-2.3.0\n"
+          ]
+        }
+      ],
+      "source": [
+        "# https://github.com/oobabooga/text-generation-webui/issues/4238\n",
+        "!pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.0/flash_attn-2.3.0+cu117torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "3xU248nEtTxg"
+      },
+      "source": [
+        "Start the training process (fine-tuning)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "19jClLyTbumJ",
+        "outputId": "9b74bad8-956d-4434-953a-d5a5be229043"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "2023-11-18 10:15:30.581758: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+            "2023-11-18 10:15:30.581829: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+            "2023-11-18 10:15:30.581870: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+            "2023-11-18 10:15:32.302565: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+            "/usr/local/lib/python3.10/dist-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations\n",
+            "  warnings.warn(\n",
+            "                                 dP            dP   dP \n",
+            "                                 88            88   88 \n",
+            "      .d8888b. dP.  .dP .d8888b. 88 .d8888b. d8888P 88 \n",
+            "      88'  `88  `8bd8'  88'  `88 88 88'  `88   88   88 \n",
+            "      88.  .88  .d88b.  88.  .88 88 88.  .88   88   88 \n",
+            "      `88888P8 dP'  `dP `88888P' dP `88888P'   dP   dP \n",
+            "                                                       \n",
+            "                                                       \n",
+            "\n",
+            "\u001b[33m[2023-11-18 10:15:36,028] [WARNING] [axolotl.validate_config:169] [PID:4655] [RANK:0] eval_batch_size != micro_batch_size. This can lead to VRAM instability.\u001b[39m\n",
+            "[2023-11-18 10:15:36,239] [INFO] [axolotl.normalize_config:128] [PID:4655] [RANK:0] GPU memory usage baseline: 0.000GB (+0.255GB misc)\u001b[39m\n",
+            "\u001b[33m[2023-11-18 10:15:36,239] [WARNING] [axolotl.scripts.check_accelerate_default_config:343] [PID:4655] [RANK:0] accelerate config file found at /root/.cache/huggingface/accelerate/default_config.yaml. This can lead to unexpected errors\u001b[39m\n",
+            "\u001b[33m[2023-11-18 10:15:36,239] [WARNING] [axolotl.scripts.check_user_token:355] [PID:4655] [RANK:0] Error verifying HuggingFace token. Remember to log in using `huggingface-cli login` and get your access token from https://huggingface.co/settings/tokens if you want to use gated models or datasets.\u001b[39m\n",
+            "[2023-11-18 10:15:36,594] [DEBUG] [axolotl.load_tokenizer:100] [PID:4655] [RANK:0] EOS: 2 / </s>\u001b[39m\n",
+            "[2023-11-18 10:15:36,595] [DEBUG] [axolotl.load_tokenizer:101] [PID:4655] [RANK:0] BOS: 1 / <s>\u001b[39m\n",
+            "[2023-11-18 10:15:36,595] [DEBUG] [axolotl.load_tokenizer:102] [PID:4655] [RANK:0] PAD: 0 / <unk>\u001b[39m\n",
+            "[2023-11-18 10:15:36,595] [DEBUG] [axolotl.load_tokenizer:103] [PID:4655] [RANK:0] UNK: 0 / <unk>\u001b[39m\n",
+            "[2023-11-18 10:15:36,595] [INFO] [axolotl.load_tokenized_prepared_datasets:147] [PID:4655] [RANK:0] Unable to find prepared dataset in last_run_prepared/5dca4483042d16053f3cd9eeaf5ac8af\u001b[39m\n",
+            "[2023-11-18 10:15:36,595] [INFO] [axolotl.load_tokenized_prepared_datasets:148] [PID:4655] [RANK:0] Loading raw datasets...\u001b[39m\n",
+            "[2023-11-18 10:15:36,595] [INFO] [axolotl.load_tokenized_prepared_datasets:153] [PID:4655] [RANK:0] No seed provided, using default seed of 42\u001b[39m\n",
+            "Map (num_proc=2): 100% 846/846 [00:00<00:00, 991.41 examples/s] \n",
+            "[2023-11-18 10:15:37,890] [INFO] [axolotl.load_tokenized_prepared_datasets:355] [PID:4655] [RANK:0] merging datasets\u001b[39m\n",
+            "[2023-11-18 10:15:37,892] [INFO] [axolotl.load_tokenized_prepared_datasets:362] [PID:4655] [RANK:0] Saving merged prepared dataset to disk... last_run_prepared/5dca4483042d16053f3cd9eeaf5ac8af\u001b[39m\n",
+            "Saving the dataset (1/1 shards): 100% 846/846 [00:00<00:00, 118881.71 examples/s]\n",
+            "Filter (num_proc=2): 100% 803/803 [00:00<00:00, 3171.26 examples/s]\n",
+            "Filter (num_proc=2): 100% 43/43 [00:00<00:00, 301.68 examples/s]\n",
+            "Map (num_proc=2): 100% 803/803 [00:00<00:00, 2783.35 examples/s]\n",
+            "[2023-11-18 10:15:38,745] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] total_num_tokens: 77893\u001b[39m\n",
+            "[2023-11-18 10:15:38,753] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] `total_supervised_tokens: 77893`\u001b[39m\n",
+            "[2023-11-18 10:15:44,265] [INFO] [axolotl.utils.samplers.multipack._len_est:178] [PID:4655] [RANK:0] packing_efficiency_estimate: 1.0 total_num_tokens per device: 77893\u001b[39m\n",
+            "[2023-11-18 10:15:44,265] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] data_loader_len: 8\u001b[39m\n",
+            "[2023-11-18 10:15:44,265] [INFO] [axolotl.log:60] [PID:4655] [RANK:0] sample_packing_eff_est across ranks: [0.95084228515625]\u001b[39m\n",
+            "[2023-11-18 10:15:44,265] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] sample_packing_eff_est: 0.96\u001b[39m\n",
+            "[2023-11-18 10:15:44,266] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] total_num_steps: 32\u001b[39m\n",
+            "[2023-11-18 10:15:44,266] [DEBUG] [axolotl.train.log:60] [PID:4655] [RANK:0] loading tokenizer... NousResearch/Llama-2-7b-hf\u001b[39m\n",
+            "[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:100] [PID:4655] [RANK:0] EOS: 2 / </s>\u001b[39m\n",
+            "[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:101] [PID:4655] [RANK:0] BOS: 1 / <s>\u001b[39m\n",
+            "[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:102] [PID:4655] [RANK:0] PAD: 0 / <unk>\u001b[39m\n",
+            "[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:103] [PID:4655] [RANK:0] UNK: 0 / <unk>\u001b[39m\n",
+            "[2023-11-18 10:15:44,630] [DEBUG] [axolotl.train.log:60] [PID:4655] [RANK:0] loading model and peft_config...\u001b[39m\n",
+            "[2023-11-18 10:15:44,713] [INFO] [axolotl.load_model:201] [PID:4655] [RANK:0] patching _expand_mask\u001b[39m\n",
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+            "Downloading shards: 100% 2/2 [01:29<00:00, 44.56s/it]\n",
+            "Loading checkpoint shards:  50% 1/2 [01:07<01:07, 67.16s/it]"
+          ]
+        }
+      ],
+      "source": [
+        "!accelerate launch -m axolotl.cli.train model.yml --load_in_8bit=False"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Ff33I_IOy3A1"
+      },
+      "outputs": [],
+      "source": [
+        "!python3 -m axolotl.cli.merge_lora model.yml --lora_model_dir=\"./qlora-out\" --load_in_8bit=False --load_in_4bit=False"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "SVvJ01EhzRys"
+      },
+      "outputs": [],
+      "source": [
+        "\n",
+        "!git clone https://github.com/ggerganov/llama.cpp.git\n",
+        "!cd llama.cpp && make LLAMA_CUBLAS=1\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Bl7P2PPA0gsD"
+      },
+      "outputs": [],
+      "source": [
+        "\n",
+        "# We need to convert the pytorch model into ggml for quantization\n",
+        "# It crates 'ggml-model-f16.bin' in the 'merged' directory.\n",
+        "!cd llama.cpp && python convert.py --outtype f16 \\\n",
+        "    /content/qlora-out/merged/pytorch_model-00001-of-00002.bin\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6OZq8KGP0kUg"
+      },
+      "outputs": [],
+      "source": [
+        "\n",
+        "# Start off by making a basic q4_0 4-bit quantization.\n",
+        "# It's important to have 'ggml' in the name of the quant for some\n",
+        "# software to recognize it's file format.\n",
+        "!cd llama.cpp &&  ./quantize /content/qlora-out/merged/ggml-model-f16.gguf \\\n",
+        "    /content/custom-model-q4_0.bin q4_0"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}