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To begin, install llama.cpp
by following the instructions on their GitHub page.
To start the server, use the following command:
./llama-server -m your_model.gguf --port 8080
You can check if it's running by visiting http://localhost:8080.
Edit the prompts in promptfooconfig.yaml
.
Run the evaluation:
npx promptfoo@latest eval
View the results:
npx promptfoo@latest view
llama.cpp
supports many models that can be converted to the GGUF format. We recommend downloading models from Hugging Face. You may need to authenticate with your Hugging Face account using their CLI to download models.
We do not format the prompts for compatibility with llama.cpp
. Prompts are passed as-is. Refer to the documentation or model card for the specific model you are using to ensure compatibility with its interface. We provide various formatting examples to illustrate different ways to format your prompts.
Since promptfoo is unaware of the underlying model being run in llama.cpp
, it will not invalidate the cache when the model is updated. This means you may see stale results from the cache if you change the model. Run npx promptfoo@latest eval --no-cache
to perform the evaluation without using the cache.
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Browsing data directories saved to Azure Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!
promptfoo is now integrated with Azure Cloud Storage!
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Browsing data directories saved to S3 compatible storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!
promptfoo is now integrated with your S3 compatible storage!
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