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---
library_name: transformers
tags:
- llama
- facebook
- meta
- llama-2
- conversational
- text-generation-inference
---
A quantization of [meta-llama/Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b) using [PV-Tuning](https://arxiv.org/abs/2405.14852) on top of [AQLM](https://arxiv.org/abs/2401.06118) quantization
For this quantization, we used 1 codebook of 16 bits for groups of 8 weights.
| Model | AQLM scheme | WikiText 2 PPL | Model size, Gb | Hub link |
|------------|-------------|----------------|----------------|--------------------------------------------------------------------------|
| Llama-2-7b (this) | 1x16g8 | 5.68 | 2.4 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-1x16-hf) |
| Llama-2-7b | 2x8g8 | 5.90 | 2.2 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-2x8-hf) |
| Llama-2-13b| 1x16g8 | 5.05 | 4.1 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-13b-AQLM-PV-2Bit-1x16-hf)|
| Llama-2-70b| 1x16g8 | 3.78 | 18.8 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-70b-AQLM-PV-2Bit-1x16-hf)|
The 1x16g16 (1-bit) models are on the way, as soon as we update the inference lib with their respective kernels.
To learn more about the inference, as well as the information on how to quantize models yourself, please refer to the [official GitHub repo](https://github.com/Vahe1994/AQLM).
The original code for PV-Tuning can be found in the [AQLM@pv-tuning](https://github.com/Vahe1994/AQLM/tree/pv-tuning) branch.
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