vbatts/llama.cpp
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chore: add references to the quantisation space.

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Vaibhav Srivastav 2024-05-14 23:01:11 +02:00
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README.md
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@ -712,6 +712,10 @@ Building the program with BLAS support may lead to some performance improvements
### Prepare and Quantize ### Prepare and Quantize
Note: You can use the [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space on Hugging Face to quantise your model weights without any setup too.
It is synced to `llama.cpp` main every 6 hours.
To obtain the official LLaMA 2 weights please see the <a href="#obtaining-and-using-the-facebook-llama-2-model">Obtaining and using the Facebook LLaMA 2 model</a> section. There is also a large selection of pre-quantized `gguf` models available on Hugging Face. To obtain the official LLaMA 2 weights please see the <a href="#obtaining-and-using-the-facebook-llama-2-model">Obtaining and using the Facebook LLaMA 2 model</a> section. There is also a large selection of pre-quantized `gguf` models available on Hugging Face.
Note: `convert.py` does not support LLaMA 3, you can use `convert-hf-to-gguf.py` with LLaMA 3 downloaded from Hugging Face. Note: `convert.py` does not support LLaMA 3, you can use `convert-hf-to-gguf.py` with LLaMA 3 downloaded from Hugging Face.

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examples/quantize/README.md
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@ -1,6 +1,8 @@
# quantize # quantize
TODO You can also use the [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space on Hugging Face to build your own quants without any setup.
Note: It is synced to llama.cpp `main` every 6 hours.
## Llama 2 7B ## Llama 2 7B