Update dependency @huggingface/transformers to v3.2.4

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
@huggingface/transformers	3.2.3 -> 3.2.4

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Release Notes

huggingface/transformers.js (@​huggingface/transformers)

v3.2.4

Compare Source

What's new?

• Add support for visualizing self-attention heatmaps in https://github.com/huggingface/transformers.js/pull/1117

  Example code

  import { AutoProcessor, AutoModelForImageClassification, interpolate_4d, RawImage } from "@​huggingface/transformers";
  
  // Load model and processor
  const model_id = "onnx-community/dinov2-with-registers-small-with-attentions";
  const model = await AutoModelForImageClassification.from_pretrained(model_id);
  const processor = await AutoProcessor.from_pretrained(model_id);
  
  // Load image from URL
  const image = await RawImage.read("https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg");
  
  // Pre-process image
  const inputs = await processor(image);
  
  // Perform inference
  const { logits, attentions } = await model(inputs);
  
  // Get the predicted class
  const cls = logits[0].argmax().item();
  const label = model.config.id2label[cls];
  console.log(`Predicted class: ${label}`);
  
  // Set config values
  const patch_size = model.config.patch_size;
  const [width, height] = inputs.pixel_values.dims.slice(-2);
  const w_featmap = Math.floor(width / patch_size);
  const h_featmap = Math.floor(height / patch_size);
  const num_heads = model.config.num_attention_heads;
  const num_cls_tokens = 1;
  const num_register_tokens = model.config.num_register_tokens ?? 0;
  
  // Visualize attention maps
  const selected_attentions = attentions
      .at(-1) // we are only interested in the attention maps of the last layer
      .slice(0, null, 0, [num_cls_tokens + num_register_tokens, null])
      .view(num_heads, 1, w_featmap, h_featmap);
  
  const upscaled = await interpolate_4d(selected_attentions, {
      size: [width, height],
      mode: "nearest",
  });
  
  for (let i = 0; i < num_heads; ++i) {
      const head_attentions = upscaled[i];
      const minval = head_attentions.min().item();
      const maxval = head_attentions.max().item();
      const image = RawImage.fromTensor(
          head_attentions
              .sub_(minval)
              .div_(maxval - minval)
              .mul_(255)
              .to("uint8"),
      );
      await image.save(`attn-head-${i}.png`);
  }

• Add min, max, argmin, argmax tensor ops for dim=null

• Add support for nearest-neighbour interpolation in interpolate_4d

• Depth Estimation pipeline improvements (faster & returns resized depth map)

• TypeScript improvements by @​ocavue and @​shrirajh in https://github.com/huggingface/transformers.js/pull/1081 and https://github.com/huggingface/transformers.js/pull/1122

• Remove unused imports from tokenizers.js by @​pratapvardhan in https://github.com/huggingface/transformers.js/pull/1116

New Contributors

• @​shrirajh made their first contribution in https://github.com/huggingface/transformers.js/pull/1122
• @​pratapvardhan made their first contribution in https://github.com/huggingface/transformers.js/pull/1116

Full Changelog: huggingface/transformers.js@3.2.3...3.2.4

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