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@ -36,7 +36,8 @@ llama-cli --model <model_path> --instruction <instruction> [--input <input>] [--
| temperature | TEMPERATURE | 0.95 | Sampling temperature for model output. |
| top_p | TOP_P | 0.85 | The cumulative probability for top-p sampling. |
| top_k | TOP_K | 20 | The number of top-k tokens to consider for text generation. |
| context-size | CONTEXT_SIZE | 512 | Default token context size. |
| alpaca | ALPACA | true | Set to true for alpaca models. |
Here's an example of using `llama-cli`:
@ -81,6 +82,8 @@ The API takes takes the following:
| model | MODEL_PATH | | The path to the pre-trained GPT-based model. |
| threads | THREADS | CPU cores | The number of threads to use for text generation. |
| address | ADDRESS | :8080 | The address and port to listen on. |
| context-size | CONTEXT_SIZE | 512 | Default token context size. |
| alpaca | ALPACA | true | Set to true for alpaca models. |
Once the server is running, you can make requests to it using HTTP. For example, to generate text based on an instruction, you can send a POST request to the `/predict` endpoint with the instruction as the request body:
@ -97,26 +100,30 @@ curl --location --request POST 'http://localhost:8080/predict' --header 'Content
## Using other models
You can use the lite images ( for example `quay.io/go-skynet/llama-cli:v0.2-lite`) that don't ship any model, and specify a model binary to be used for inference with `--model`.
13B and 30B models are known to work:
### 13B
```
# Download the model image, extract the model
docker run --name model --entrypoint /models quay.io/go-skynet/models:ggml2-alpaca-13b-v0.2
docker cp model:/models/model.bin ./
# Use the model with llama-cli
docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2 api --model /models/model.bin
docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2-lite api --model /models/model.bin
```
### 30B
```
# Download the model image, extract the model
docker run --name model --entrypoint /models quay.io/go-skynet/models:ggml2-alpaca-30b-v0.2
docker cp model:/models/model.bin ./
# Use the model with llama-cli
docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2 api --model /models/model.bin
docker run -v $PWD:/models -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:v0.2-lite api --model /models/model.bin
```
### Golang client API