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Update examples/quantization_24_sparse_w4a16 README #52

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Aug 5, 2024
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Update examples/quantization_24_sparse_w4a16 README #52

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4 changes: 2 additions & 2 deletions examples/quantization_24_sparse_w4a16/README.md
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Expand Up @@ -19,7 +19,7 @@ pip install -e .
The example includes an end-to-end script for applying the quantization algorithm.

```bash
python3 llama2_24sparse_example.py
python3 llama7b_sparse_w4a16.py
```


Expand All @@ -29,7 +29,7 @@ This example uses LLMCompressor and Compressed-Tensors to create a 2:4 sparse an
The model is calibrated and trained with the ultachat200k dataset.
At least 75GB of GPU memory is required to run this example.

Follow the steps below, or to run the example as `python examples/llama7b_sparse_quantized/llama7b_sparse_w4a16.py`
Follow the steps below, or to run the example as `python examples/quantization_24_sparse_w4a16/llama7b_sparse_w4a16.py`

## Step 1: Select a model, dataset, and recipe
In this step, we select which model to use as a baseline for sparsification, a dataset to
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