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Readme modification #1700

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@libinta libinta commented Jan 16, 2025

Simplify ReadMe for text-classification, text-feature-extraction, and image-to-text.

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Fixes # (issue)

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  • This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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@libinta libinta requested a review from regisss as a code owner January 16, 2025 23:04
@@ -17,55 +17,11 @@ limitations under the License.
# Image to Text Examples
This directory contains a script that showcases how to perform image to text generation on Intel® Gaudi® AI Accelerators.

## Single-HPU inference
Habana FusedSDPA is a fused and optimized implementation of torch.nn.functional.scaled_dot_product_attention() for Gaudi. For more details, refer to [Gaudi online documentation](https://docs.habana.ai/en/latest/PyTorch/Model_Optimization_PyTorch/Optimization_in_PyTorch_Models.html?highlight=fusedsdpa#using-fused-scaled-dot-product-attention-fusedsdpa). We optimized many models with FusedSDPA optimization as in optimum/habana/transformers/models. If models are not optimzied with FusedSDPA, it uses SDPA implementation.

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Comment on lines 30 to 39
Finetune model can be done as single device, multi-devices with mpi or deepspeed.

For multi-devices training with mpi, add the following before run_glue.py where X is device number
> python ../gaudi_spawn.py \
> --world_size X --use_mpi run_glue.py \

For multi-devices training with deepspeed, add the following before run_glue.py and deepspeed config with --deepspeed after where X is device number
> python ../gaudi_spawn.py \
> --world_size X --use_deepspeed run_glue.py --deepspeed \

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@libinta libinta requested a review from schoi-habana January 16, 2025 23:28
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some typo fixes suggested- pls see

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couple links need fixing

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@libinta libinta added the run-test Run CI for PRs from external contributors label Jan 18, 2025
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--bf16 \
--sdp_on_bf16
```
Inference with FP8 precision are enabled using [Intel Neural Compressor (INC)](https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Inference_Using_FP8.html), which provides model measurement and quantization capabilities in PyTorch.
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```
Inference with FP8 precision are enabled using [Intel Neural Compressor (INC)](https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Inference_Using_FP8.html), which provides model measurement and quantization capabilities in PyTorch.
More information on enabling FP8 in SynapseAI is available here:
https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Inference_Using_FP8.html
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Same

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