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Remove --fp8 flag from README #966

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Remove --fp8 flag from README #966

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6 changes: 0 additions & 6 deletions examples/text-generation/README.md
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Expand Up @@ -107,7 +107,6 @@ Here are a few settings you may be interested in:
- `--prompt` to benchmark the model on one or several prompts of your choice
- `--attn_softmax_bf16` to run attention softmax layer in bfloat16 precision provided that the model (such as Llama) supports it
- `--trim_logits` to calculate logits only for the last token in the first time step provided that the model (such as Llama) supports it
- `--fp8` Enable Quantization to fp8

For example, you can reproduce the results presented in [this blog post](https://huggingface.co/blog/habana-gaudi-2-bloom) with the following command:
```bash
Expand Down Expand Up @@ -284,7 +283,6 @@ QUANT_CONFIG=./quantization_config/maxabs_quant.json python ../gaudi_spawn.py \
--reuse_cache \
--bf16 \
--batch_size 1 \
--fp8
```

Alternatively, here is another example to quantize the model based on previous measurements for LLama2-70b:
Expand All @@ -302,7 +300,6 @@ QUANT_CONFIG=./quantization_config/maxabs_quant.json python ../gaudi_spawn.py \
--max_new_tokens 2048 \
--max_input_tokens 2048 \
--limit_hpu_graphs \
--fp8
```

Here is an example to measure the tensor quantization statistics on Mixtral-8x7B with 1 card:
Expand All @@ -329,7 +326,6 @@ QUANT_CONFIG=./quantization_config/maxabs_quant_mixtral.json python run_generati
--max_new_tokens 2048 \
--batch_size 16 \
--bf16 \
--fp8
```

Here is an example to measure the tensor quantization statistics on Falcon-180B with 8 cards:
Expand Down Expand Up @@ -361,9 +357,7 @@ QUANT_CONFIG=./quantization_config/maxabs_quant.json python ../gaudi_spawn.py \
--bf16 \
--reuse_cache \
--trim_logits \
--fp8
```
`--fp8` is required to enable quantization in fp8.


### Using Habana Flash Attention
Expand Down