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Added AutoGPTQ UINT4 to README.md #279

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24 changes: 24 additions & 0 deletions examples/text-generation/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -506,6 +506,30 @@ python ../gaudi_spawn.py --use_deepspeed --world_size 8 run_generation.py \

For more details see [documentation](https://docs.habana.ai/en/latest/PyTorch/Model_Optimization_PyTorch/Optimization_in_PyTorch_Models.html#using-fused-sdpa).

### Running with UINT4 using AutoGPTQ


Llama2-7b in UINT4 is enabled using [AutoGPTQ Fork](https://github.com/HabanaAI/AutoGPTQ), which provides quantization capabilities in PyTorch.
Currently, the support is for UINT4 inference of pre-quantized models only.

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You can run a *UINT4 quantized* model using AutoGPTQ with the argument `--gptq`.

Here is an example to run a quantized model on Llama2-7b `TheBloke/Llama-2-7b-Chat-GPTQ`:
```bash
python run_generation.py \
--attn_softmax_bf16 \
--model_name_or_path TheBloke/Llama-2-7b-Chat-GPTQ \
--use_hpu_graphs \
--limit_hpu_graphs \
--use_kv_cache \
--bucket_size 128 \
--bucket_internal \
--trim_logits \
--max_new_tokens 128 \
--batch_size 1 \
--bf16 \
--gptq
```

## Language Model Evaluation Harness

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