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few typos and clarity changes (#91) (#92)

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Co-authored-by: antongisli <anton@huge.geek.nz>
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Ettore Di Giacinto 2023-04-27 07:47:39 +02:00 committed by GitHub
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@ -5,7 +5,7 @@
<br>
</h1>
> :warning: This project has been renamed from `llama-cli` to `LocalAI` to reflect the fact that we are focusing on a fast drop-in OpenAI API rather on the CLI interface. We think that there are already many projects that can be used as a CLI interface already, for instance [llama.cpp](https://github.com/ggerganov/llama.cpp) and [gpt4all](https://github.com/nomic-ai/gpt4all). If you are were using `llama-cli` for CLI interactions and want to keep using it, use older versions or please open up an issue - contributions are welcome!
> :warning: This project has been renamed from `llama-cli` to `LocalAI` to reflect the fact that we are focusing on a fast drop-in OpenAI API rather than on the CLI interface. We think that there are already many projects that can be used as a CLI interface already, for instance [llama.cpp](https://github.com/ggerganov/llama.cpp) and [gpt4all](https://github.com/nomic-ai/gpt4all). If you are using `llama-cli` for CLI interactions and want to keep using it, use older versions or please open up an issue - contributions are welcome!
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
@ -123,10 +123,10 @@ To see other examples on how to integrate with other projects, see: [examples](h
The API doesn't inject a default prompt for talking to the model. You have to use a prompt similar to what's described in the standford-alpaca docs: https://github.com/tatsu-lab/stanford_alpaca#data-release.
<details>
You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibiling file, `foo.bin.tmpl` which will be used as a default prompt, for instance this can be used with alpaca:
You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibling file, `foo.bin.tmpl` which will be used as a default prompt and can be used with alpaca:
```
Below is an instruction that describes a task. Write a response that appropriately completes the request.
The below instruction describes a task. Write a response that appropriately completes the request.
### Instruction:
{{.Input}}
@ -134,7 +134,7 @@ Below is an instruction that describes a task. Write a response that appropriate
### Response:
```
See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for most popular models.
See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for some of the most popular models.
</details>
@ -149,7 +149,7 @@ Example of starting the API with `docker`:
docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
```
And you'll see:
You should see:
```
┌───────────────────────────────────────────────────┐
│ Fiber v2.42.0 │
@ -192,7 +192,7 @@ Following the list of endpoints/parameters supported.
Note:
- You can also specify the model a part of the OpenAI token.
- You can also specify the model as part of the OpenAI token.
- If only one model is available, the API will use it for all the requests.
#### Chat completions
@ -214,7 +214,7 @@ Available additional parameters: `top_p`, `top_k`, `max_tokens`
#### Completions
<details>
For example, to generate a completion, you can send a POST request to the `/v1/completions` endpoint with the instruction as the request body:
To generate a completion, you can send a POST request to the `/v1/completions` endpoint with the instruction as per the request body:
```
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",