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Bump @huggingface/transformers from 3.8.1 to 4.0.1#118

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Bump @huggingface/transformers from 3.8.1 to 4.0.1#118
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@dependabot dependabot bot commented on behalf of github Apr 6, 2026

Bumps @huggingface/transformers from 3.8.1 to 4.0.1.

Release notes

Sourced from @​huggingface/transformers's releases.

4.0.0

🚀 Transformers.js v4

We're excited to announce that Transformers.js v4 is now available on NPM! After a year of development (we started in March 2025 🤯), we're finally ready for you to use it.

npm i @huggingface/transformers

Links: YouTube Video, Blog Post, Demo Collection

New WebGPU backend

The biggest change is undoubtedly the adoption of a new WebGPU Runtime, completely rewritten in C++. We've worked closely with the ONNX Runtime team to thoroughly test this runtime across our ~200 supported model architectures, as well as many new v4-exclusive architectures.

In addition to better operator support (for performance, accuracy, and coverage), this new WebGPU runtime allows the same transformers.js code to be used across a wide variety of JavaScript environments, including browsers, server-side runtimes, and desktop applications. That's right, you can now run WebGPU-accelerated models directly in Node, Bun, and Deno!

We've proven that it's possible to run state-of-the-art AI models 100% locally in the browser, and now we're focused on performance: making these models run as fast as possible, even in resource-constrained environments. This required completely rethinking our export strategy, especially for large language models. We achieve this by re-implementing new models operation by operation, leveraging specialized ONNX Runtime Contrib Operators like com.microsoft.GroupQueryAttention, com.microsoft.MatMulNBits, or com.microsoft.QMoE to maximize performance.

For example, adopting the com.microsoft.MultiHeadAttention operator, we were able to achieve a ~4x speedup for BERT-based embedding models.

New models

Thanks to our new export strategy and ONNX Runtime's expanding support for custom operators, we've been able to add many new models and architectures to Transformers.js v4. These include popular models like GPT-OSS, Chatterbox, GraniteMoeHybrid, LFM2-MoE, HunYuanDenseV1, Apertus, Olmo3, FalconH1, and Youtu-LLM. Many of these required us to implement support for advanced architectural patterns, including Mamba (state-space models), Multi-head Latent Attention (MLA), and Mixture of Experts (MoE). Perhaps most importantly, these models are all compatible with WebGPU, allowing users to run them directly in the browser or server-side JavaScript environments with hardware acceleration. We've released several Transformers.js v4 demos so far... and we'll continue to release more!

Additionally, we've added support for larger models exceeding 8B parameters. In our tests, we've been able to run GPT-OSS 20B (q4f16) at ~60 tokens per second on an M4 Pro Max.

... (truncated)

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Bumps [@huggingface/transformers](https://github.com/huggingface/transformers.js) from 3.8.1 to 4.0.1.
- [Release notes](https://github.com/huggingface/transformers.js/releases)
- [Commits](https://github.com/huggingface/transformers.js/commits)

---
updated-dependencies:
- dependency-name: "@huggingface/transformers"
  dependency-version: 4.0.1
  dependency-type: direct:development
  update-type: version-update:semver-major
...

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