Add ExecuTorch WebGPU program for smolvlm-500m-instruct

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+vlm_decoder.pte filter=lfs diff=lfs merge=lfs -text
+vlm_prefill.pte filter=lfs diff=lfs merge=lfs -text
+vlm_vision_q8.pte filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,202 @@
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NOTICE

@@ -0,0 +1,6 @@
+This repository contains a modified version of HuggingFaceTB/SmolVLM-500M-Instruct.
+
+Modifications by Meta Platforms, Inc.: conversion to the ExecuTorch program format (.pte) for the
+ExecuTorch WebGPU backend, and quantization as described in README.md.
+
+The original work and these modifications are distributed under the license in LICENSE.

README.md

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+---
+license: apache-2.0
+base_model:
+- HuggingFaceTB/SmolVLM-500M-Instruct
+base_model_relation: quantized
+library_name: executorch
+pipeline_tag: image-text-to-text
+tags:
+- executorch
+- webgpu
+- on-device
+- browser
+---
+# SmolVLM 500M Instruct for ExecuTorch WebGPU
+
+This repository contains an [ExecuTorch](https://github.com/pytorch/executorch) conversion of
+[HuggingFaceTB/SmolVLM-500M-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-500M-Instruct) for the ExecuTorch **WebGPU** backend, so the model runs entirely in a web browser on
+the visitor's GPU. It powers the corresponding demo in the
+[ExecuTorch Playground](https://executorch.ai/playground/webgpu/).
+
+- **Base model:** [HuggingFaceTB/SmolVLM-500M-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-500M-Instruct)
+- **Format:** ExecuTorch `.pte` programs delegated to the WebGPU backend
+- **Quantization:** int8 vision encoder and token embeddings; decoder as exported
+- **Total size:** 893.9 MB
+
+## Files
+
+| File | Size | SHA-256 |
+|---|---|---|
+| `embed_tokens.i8.bin` | 45.1 MB | `d3ea47247be0b070…` |
+| `embed_tokens.scale.f32.bin` | 192.5 KB | `adefdadaae81d572…` |
+| `tokenizer/special_tokens_map.json` | 1.0 KB | `aa0ff906077086df…` |
+| `tokenizer/tokenizer.json` | 3.4 MB | `5ece781dc8d2b2f3…` |
+| `tokenizer/tokenizer_config.json` | 27.6 KB | `36c6fd44d07d10fd…` |
+| `vlm_decoder.pte` | 370.7 MB | `d92697a8c32eeaa1…` |
+| `vlm_meta.json` | 201 B | `b36fcf7ef7da8c2a…` |
+| `vlm_prefill.pte` | 370.7 MB | `1e8671eb77ae2f60…` |
+| `vlm_vision_q8.pte` | 103.8 MB | `5f09d6028d9bb945…` |
+
+Full checksums are in `manifest.json`. The playground verifies them after download.
+
+## Running it
+
+These programs need the ExecuTorch WebGPU runtime compiled to WebAssembly
+([backends/webgpu](https://github.com/pytorch/executorch/tree/main/backends/webgpu)). The easiest way to
+try the model is the [ExecuTorch Playground](https://executorch.ai/playground/webgpu/), which downloads these
+files once, caches them in the browser, and runs everything locally.
+
+## Provenance
+
+- Converted from the upstream checkpoint with ExecuTorch's WebGPU export path.
+- Upstream revision: _to be recorded at export time_.
+- Export recipe: _to be published with the ExecuTorch release that ships the WebGPU runtime_.
+
+## License
+
+This is a derivative of the upstream model and is distributed under the same terms
+(`apache-2.0`); see `LICENSE`.
+Modifications (conversion to the ExecuTorch format and quantization) by Meta Platforms, Inc.

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manifest.json

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+  "model": "smolvlm-500m-instruct",
+  "repo": "executorch-community/SmolVLM-500M-Instruct-ExecuTorch-WebGPU",
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+}

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