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Phi-3.5-vision-instruct: Uncaught RuntimeError: Aborted(). Build with -sASSERTIONS for more info #1144

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kungfooman opened this issue Jan 13, 2025 · 0 comments
Open
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Phi-3.5-vision-instruct: Uncaught RuntimeError: Aborted(). Build with -sASSERTIONS for more info #1144

kungfooman opened this issue Jan 13, 2025 · 0 comments
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@kungfooman
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System Info

@huggingface/transformers@3.2.4
Browser: Chromium Version 133.0.6845.0 (Entwickler-Build) (64-Bit)
Node/bundler: none, simple HTML setup

Environment/Platform

  • Website/web-app
  • Browser extension
  • Server-side (e.g., Node.js, Deno, Bun)
  • Desktop app (e.g., Electron)
  • Other (e.g., VSCode extension)

Description

I just wanted to test your work on #1094

I took the example code and simply turned it into something you can just put into a HTML and run it.

But the result is:

Image

Do you have any idea what's going on? It seems to load the entire model, then trying to load it, but just crashing shortly after.

Reproduction

<body>
<script type="module">
import {
  AutoProcessor,
  AutoModelForCausalLM,
  TextStreamer,
  load_image,
} from "https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.2.4";
// Load processor and model
const model_id = "onnx-community/Phi-3.5-vision-instruct";
const processor = await AutoProcessor.from_pretrained(model_id, {
  legacy: true, // Use legacy to match python version
});
const model = await AutoModelForCausalLM.from_pretrained(model_id, {
  dtype: {
    vision_encoder: "q4", // 'q4' or 'q4f16'
    prepare_inputs_embeds: "q4", // 'q4' or 'q4f16'
    model: "q4f16", // 'q4f16'
  },
});
// Load image
const image = await load_image("https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/meme.png");
// Prepare inputs
const messages = [
  { role: "user", content: "<|image_1|>What's funny about this image?" },
];
const prompt = processor.tokenizer.apply_chat_template(messages, {
  tokenize: false,
  add_generation_prompt: true,
});
const inputs = await processor(prompt, image, { num_crops: 4 });
// (Optional) Set up text streamer
const streamer = new TextStreamer(processor.tokenizer, {
  skip_prompt: true,
  skip_special_tokens: true,
});
// Generate response
const output = await model.generate({
  ...inputs,
  streamer,
  max_new_tokens: 256,
});
</script>
</body>
@kungfooman kungfooman added the bug Something isn't working label Jan 13, 2025
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@kungfooman