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      README.md

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## :camel: llama-cli
llama-cli is a straightforward golang CLI interface for [llama.cpp](https://github.com/ggerganov/llama.cpp), providing a simple API and a command line interface that allows text generation using a GPT-based model like llama directly from the terminal.
llama-cli is a straightforward golang CLI interface for [llama.cpp](https://github.com/ggerganov/llama.cpp), providing a simple API and a command line interface that allows text generation using a GPT-based model like llama directly from the terminal. It is also compatible with [gpt4all](https://github.com/nomic-ai/gpt4all) and [alpaca](https://github.com/tatsu-lab/stanford_alpaca).
`llama-cli` uses https://github.com/go-skynet/llama, which is a fork of [llama.cpp](https://github.com/ggerganov/llama.cpp) providing golang binding.
## Container images
To begin, run:
```
docker run -ti --rm quay.io/go-skynet/llama-cli:v0.3 --instruction "What's an alpaca?" --topk 10000
docker run -ti --rm quay.io/go-skynet/llama-cli:v0.4 --instruction "What's an alpaca?" --topk 10000 --model ...
```
You will receive a response like the following:
@ -55,7 +57,7 @@ This will generate text based on the given model and instruction.
Example of starting the API with `docker`:
```bash
docker run -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.3 api --context-size 700 --threads 4
docker run -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.4 api --context-size 700 --threads 4
```
And you'll see:
@ -120,10 +122,10 @@ You can specify a model binary to be used for inference with `--model`.
```
# Download the model image, extract the model
# Use the model with llama-cli
docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.3-lite api --model /models/model.bin
docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.4 api --model /models/model.bin
```
gpt4all (https://github.com/nomic-ai/gpt4all) works as well, however the original model needs to be converted:
gpt4all (https://github.com/nomic-ai/gpt4all) works as well, however the original model needs to be converted (same applies for old alpaca models, too):
```bash
wget -O tokenizer.model https://huggingface.co/decapoda-research/llama-30b-hf/resolve/main/tokenizer.model
@ -132,6 +134,7 @@ cp gpt4all.. models/
git clone https://gist.github.com/eiz/828bddec6162a023114ce19146cb2b82
pip install sentencepiece
python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.model
# There will be a new model with the ".tmp" extension, you have to use that one!
```
### Golang client API
@ -189,3 +192,14 @@ docker run --privileged -v /var/run/docker.sock:/var/run/docker.sock --rm -t -v
# run the binary
./llama-cli --instruction "What's an alpaca?"
```
## License
MIT
## Acknowledgements
- [llama.cpp](https://github.com/ggerganov/llama.cpp)
- https://github.com/tatsu-lab/stanford_alpaca
- https://github.com/cornelk/llama-go for the initial ideas
- https://github.com/antimatter15/alpaca.cpp for the light model version (this is compatible and tested only with that checkpoint model!)
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