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update readme for the run-model-locally section #126

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7 changes: 5 additions & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -29,10 +29,13 @@ Try out the models immediately without downloading anything in Our [Huggingface

## Run Rubra Models Locally

Check out our [documentation](https://docs.rubra.ai/category/serving--inferencing) to learn how to run Rubra models locally.
We extend the following inferencing tools to run Rubra models in an OpenAI-compatible tool-calling format for local use:

- [llama.cpp](https://github.com/ggerganov/llama.cpp)
- [vllm](https://github.com/vllm-project/vllm)
- [llama.cpp](https://github.com/rubra-ai/tools.cpp)
- [vLLM](https://github.com/rubra-ai/vllm)

**Note**: Llama3 models, including the 8B and 70B variants, are known to experience increased perplexity and a subsequent degradation in function-calling performance as a result of quantization. We recommend serving them with either vLLM or using the fp16 quantization.

## Benchmark

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6 changes: 4 additions & 2 deletions docs/docs/README.md
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Expand Up @@ -38,8 +38,10 @@ Try out the models immediately without downloading anything in [Huggingface Spac

We extend the following inferencing tools to run Rubra models in an OpenAI-compatible tool-calling format for local use:

- [llama.cpp](https://github.com/ggerganov/llama.cpp)
- [vllm](https://github.com/vllm-project/vllm)
- [llama.cpp](https://github.com/rubra-ai/tools.cpp)
- [vLLM](https://github.com/rubra-ai/vllm)

**Note**: Llama3 models, including the 8B and 70B variants, are known to experience increased perplexity and a subsequent degradation in function-calling performance as a result of quantization. We recommend serving them with either vLLM or using the fp16 quantization.

## Contributing

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