
Quantized Meta AI's [LLaMA](https://arxiv.org/abs/2302.13971) in 4bit with the help of [GPTQ](https://arxiv.org/abs/2210.17323v2) algorithm v2.
GPTQ implementation - https://github.com/qwopqwop200/GPTQ-for-LLaMa/tree/49efe0b67db4b40eac2ae963819ebc055da64074

Conversion process
```sh
CUDA_VISIBLE_DEVICES=0 python llama.py ./llama-7b c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors ./q4/llama7b-4bit-ts-ao-g128-v2.safetensors
```

{}
transformers llama text-generation arxiv:2302.13971 arxiv:2210.17323 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #llama #text-generation #arxiv-2302.13971 #arxiv-2210.17323 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 


Quantized Meta AI's LLaMA in 4bit with the help of GPTQ algorithm v2.
GPTQ implementation - URL

Conversion process


TAGS
#transformers #llama #text-generation #arxiv-2302.13971 #arxiv-2210.17323 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

TAGS
#transformers #llama #text-generation #arxiv-2302.13971 #arxiv-2210.17323 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
