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fixed command line arguments in docs (#1092)
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# What does this PR do?

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Just removed `--` from the arguments. 
With `--` bitsandbytes and bitsandbytes-nf4 are considered an option
which they are not

## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the
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Fluder-Paradyne authored Oct 3, 2023
1 parent 1bebb9e commit b4f68c3
Showing 1 changed file with 2 additions and 2 deletions.
4 changes: 2 additions & 2 deletions docs/source/conceptual/quantization.md
Original file line number Diff line number Diff line change
Expand Up @@ -45,15 +45,15 @@ bitsandbytes is a library used to apply 8-bit and 4-bit quantization to models.
In TGI, you can use 8-bit quantization by adding `--quantize bitsandbytes` like below 👇

```bash
docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id $model --quantize --bitsandbytes
docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id $model --quantize bitsandbytes
```

4-bit quantization is also possible with bitsandbytes. You can choose one of the following 4-bit data types: 4-bit float (`fp4`), or 4-bit `NormalFloat` (`nf4`). These data types were introduced in the context of parameter-efficient fine-tuning, but you can apply them for inference by automatically converting the model weights on load.

In TGI, you can use 4-bit quantization by adding `--quantize bitsandbytes-nf4` or `--quantize bitsandbytes-fp4` like below 👇

```bash
docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id $model --quantize --bitsandbytes-nf4
docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id $model --quantize bitsandbytes-nf4
```

You can get more information about 8-bit quantization by reading this [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), and 4-bit quantization by reading [this blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes).

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