Conversation
* ONNX Runtime improvements (experimental native webgpu; fix iOS) (#1231) * customize the wasm paths * update implementation * allow using 'webgpu' in nodejs binding * update version of onnxruntime-node * Upgrade onnxruntime-web to same version as onnxruntime-node * Update list of supported devices --------- Co-authored-by: Joshua Lochner <26504141+xenova@users.noreply.github.com> * customize the wasm paths (#1250) * customize the wasm paths * update implementation * [internal] Add is_decoder option to session retrieval for preferred output location * Update tests * Formatting * Bump ort versions * Bump onnxruntime-node version * Bump versions * Bump ORT versions * Bump versions * Only check webgpu fp16 for non-node environments * Fix * Assume node supports webgpu * Update ORT node support comment * Relax test strictness * Update conversion script versions * Downgrade onnxslim * cleanup * Update package-lock.json * Update onnxruntime versions * Update post-build script * Use built-in session release function * Call garbage collection after each tokenizer test * Do not double-throw error * Fix race-condition in build process with file removal * Update versions * Bump jinja version * [version] Update to 3.6.3 * Bump jinja version to support new features * [version] Update to 3.6.3 * Add support for LFM2 models (#1367) * Use prefix in lfm2 output location (#1369) * Update package-lock.json * Run `npm audit fix` * Add special tokens in text-generation pipeline if tokenizer requires (#1370) * Add special tokens in text-generation pipeline if tokenizer requires * Fix logits processors tests * Update bundles.test.js * Update comment * Formatting * Add support for ModernBERT Decoder (#1371) * Use from/to buffer instead of string Actually fixes #1343 * Add support for Voxtral (#1373) * Support longform voxtral processing (#1375) * [version] Update to 3.7.0 * Add support for Arcee (#1377) * Optimize tensor.slice() (#1381) * Optimize tensor.slice() The performance of executing `tensor.slice()` is super poor, especially for the 'logits' tensor with large dimensions. ``` const logits = outputs.logits.slice(null, -1, null);` ``` This is because currently implementation of the `slice` method manually iterates through each element and calculate indices which is a big time consuming if the tensor shape is large. For cases like `slice(null, -1, null)`, where the slicing operation is contiguous along certain dimensions, which can be optimized by bulk copy by using `TypeArray.subarray()` and `TypeArray.set()`. * nit * Add a few more tensor slice unit tests --------- Co-authored-by: Joshua Lochner <26504141+xenova@users.noreply.github.com> --------- Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Co-authored-by: Wanming Lin <wanming.lin@intel.com>
Collaborator
Author
|
It is time! 🔥 |
Haha I've been using v4 for months to be honest hehe |
This was referenced Feb 9, 2026
Closed
Closed
This was referenced Feb 17, 2026
Closed
Closed
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
6 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This is the official, long-awaited PR that introduces Transformers.js V4.
onnxruntime-webin nodelike environments #1406@huggingface/tokenizerslibrary.Qwen2.5-Coder-0.5B-Instructdoes not work, butonnx-community/Qwen2.5-0.5B-Instructdoes #1415See benchmarks
https://huggingface.co/onnx-community/all-MiniLM-L6-v2-ONNX:
https://huggingface.co/onnx-community/bge-base-en-v1.5-ONNX:
./src/models/), grouped by model type -- models.js is getting pretty large!Other issues:
progressproperty missing inProgressInfofromprogress_callbackofAutoModel.from_pretrained#1312