An official quantization of
meta-llama/Meta-Llama-3-8B using
PV-Tuning on top of
AQLM .
For this quantization, we used 1 codebook of 16 bits for groups of 8 weights.
Note that a large portion of this model are the 16-bit embeddings/logits matrices. You can significantly reduce the model footprint by quantizing these matrices, e.g. using bitsandbytes LLM.int8 or NF4 formats. This does not require additional training
To learn more about the inference, as well as the information on how to quantize models yourself, please refer to the
official GitHub repo.
The original code for PV-Tuning can be found in the
AQLM@pv-tuning branch.
