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Build images without model
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@ -34,5 +34,14 @@ image:
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ENTRYPOINT [ "/llama-cli" ]
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SAVE IMAGE --push $IMAGE
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lite-image:
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FROM +go-deps
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ARG IMAGE=alpaca-cli-nomodel
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COPY +build/llama-cli /llama-cli
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ENV MODEL_PATH=/model.bin
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ENTRYPOINT [ "/llama-cli" ]
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SAVE IMAGE --push $IMAGE-lite
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image-all:
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BUILD --platform=linux/amd64 --platform=linux/arm64 +image
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BUILD --platform=linux/amd64 --platform=linux/arm64 +lite-image
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24
README.md
24
README.md
@ -8,7 +8,7 @@ llama-cli is a straightforward golang CLI interface for [llama.cpp](https://gith
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The `llama-cli` [container images](https://quay.io/repository/go-skynet/llama-cli?tab=tags&tag=latest) come preloaded with the [alpaca.cpp 7B](https://github.com/antimatter15/alpaca.cpp) model, enabling you to start making predictions immediately! To begin, run:
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```
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docker run -ti --rm quay.io/go-skynet/llama-cli:v0.1 --instruction "What's an alpaca?" --topk 10000
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docker run -ti --rm quay.io/go-skynet/llama-cli:v0.2 --instruction "What's an alpaca?" --topk 10000
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```
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You will receive a response like the following:
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@ -53,7 +53,7 @@ This will generate text based on the given model and instruction.
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Example of starting the API with `docker`:
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```bash
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docker run -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.1 api
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docker run -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2 api
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```
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And you'll see:
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@ -102,29 +102,21 @@ curl --location --request POST 'http://localhost:8080/predict' --header 'Content
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### 13B
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```
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wget -O tokenizer.model https://huggingface.co/decapoda-research/llama-30b-hf/resolve/main/tokenizer.model
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mkdir models
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wget -O models/gml-model-13B-q4_0.bin https://huggingface.co/Pi3141/alpaca-13B-ggml/resolve/main/ggml-model-q4_0.bin
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git clone https://gist.github.com/eiz/828bddec6162a023114ce19146cb2b82
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python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.models
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mv models/gml-model-13B-q4_0.bin.tmp models/gml-model-13B-q4_0.bin
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docker run --name model --entrypoint /models quay.io/go-skynet/models:ggml2-alpaca-13b-v0.2
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docker cp model:/models/model.bin ./
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# Use the model with llama-cli
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docker run -v $PWD/models:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:master api --model /models/gml-model-13B-q4_0.bin
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docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2 api --model /models/model.bin
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```
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### 30B
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```
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wget -O tokenizer.model https://huggingface.co/decapoda-research/llama-30b-hf/resolve/main/tokenizer.model
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mkdir models
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wget -O models/ggml-model-30B-q4_0.bin https://huggingface.co/Pi3141/alpaca-30B-ggml/blob/main/ggml-model-q4_0.bin
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git clone https://gist.github.com/eiz/828bddec6162a023114ce19146cb2b82
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python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.models
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mv models/ggml-model-30B-q4_0.bin.tmp models/ggml-model-30B-q4_0.bin
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docker run --name model --entrypoint /models quay.io/go-skynet/models:ggml2-alpaca-30b-v0.2
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docker cp model:/models/model.bin ./
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# Use the model with llama-cli
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docker run -v $PWD/models:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:master api --model /models/ggml-model-30B-q4_0.bin
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docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2 api --model /models/model.bin
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```
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### Golang client API
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