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[jit] Remove TorchScript from doc #10825

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May 12, 2025
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[jit] Remove TorchScript from doc #10825

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2 changes: 1 addition & 1 deletion examples/demo-apps/android/LlamaDemo/docs/delegates/xnnpack_README.md
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Expand Up @@ -113,7 +113,7 @@ python -m pytorch_tokenizers.tools.llama2c.convert -t tokenizer.model -o tokeniz
### For LLaVA model
* For the Llava 1.5 model, you can get it from Huggingface [here](https://huggingface.co/llava-hf/llava-1.5-7b-hf).
* Run `examples/models/llava/install_requirements.sh` to install dependencies.
* Run the following command to generate llava.pte, tokenizer.bin and an image tensor (serialized in TorchScript) image.pt.
* Run the following command to generate llava.pte, tokenizer.bin and download an image basketball.jpg.

```
python -m executorch.examples.models.llava.export_llava --pte-name llava.pte --with-artifacts
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2 changes: 1 addition & 1 deletion examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md
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Expand Up @@ -85,7 +85,7 @@ python -m examples.models.llama.export_llama --checkpoint <path-to-your-checkpoi
### For LLaVA model
* For the Llava 1.5 model, you can get it from Huggingface [here](https://huggingface.co/llava-hf/llava-1.5-7b-hf).
* Run `examples/models/llava/install_requirements.sh` to install dependencies.
* Run the following command to generate llava.pte, tokenizer.bin and an image tensor (serialized in TorchScript) image.pt.
* Run the following command to generate llava.pte, tokenizer.bin and download an image basketball.jpg.

```
python -m executorch.examples.models.llava.export_llava --pte-name llava.pte --with-artifacts
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13 changes: 3 additions & 10 deletions examples/models/llava/README.md
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Expand Up @@ -41,10 +41,8 @@ The model weights is 15GiB, and the other memory usage at export stage (`export_

### Generate ExecuTorch .PTE and other artifacts

Run the following command to generate `llava.pte`, `tokenizer.bin` and an image
tensor (serialized in TorchScript) `image.pt`.
Run the following command to generate `llava.pte`, `tokenizer.bin` and an image `basketball.jpg`.

> **Warning**: The C++ runner `llava_main` binary cannot process raw image inputs such as JPEG, PNG, or BMP files directly. You must convert these images to a `.pt` file format using the `examples/models/llava/image_util.py` script before using them with `llava_main`.

Prerequisite: run `install_executorch.sh` to install ExecuTorch and run
`examples/models/llava/install_requirements.sh` to install dependencies.
Expand All @@ -65,11 +63,6 @@ python -m executorch.examples.models.llava.test.test_pte llava.pte
See or run `.ci/scripts/test_llava.sh` shell script to build a C++ runner. This
script also has preliminary support to build the C++ runner for Android.

This also has an image utility Python script to generate image in PyTorch
loadable format. Alternatively, we are working on generating image format which
doesn't need PyTorch to load an image. Motivation for this is to build the C++
runner on Android.

Then you should be able to find `llava_main` binary:

```bash
Expand Down Expand Up @@ -104,8 +97,8 @@ Run:
cmake-out/examples/models/llava/llava_main \
--model_path=llava.pte \
--tokenizer_path=tokenizer.bin \
--image_path=image.pt \
--prompt="ASSISTANT:" \
--image_path=basketball.jpg \
--prompt="ASSISTANT:" \
--seq_len=768 \
--temperature=0
```
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