transformers
https://github.com/huggingface/transformers
Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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- Issues
- fix(trainer): Apply weight conversions when resuming from a checkpoint
- logits_to_keep bool mask for all ForXXX classes, expose last_hidden_state, fix negative output_hidden_states indices
- [serge] Fix 2 integration tests for model `convnextv2` failing with `output_mismatch` (tensor values differ (2))
- [serge] Fix 1 integration test for model `moshi` failing with `OOM` (other (1))
- Fix skip reason for MoE padding-free test (gpt_oss, longcat_flash)
- FSDP2: evaluate/predict on a fresh Trainer raises in Accelerator.prepare
- Context parallelism: Trainer.predict returns duplicated rows, unlabeled path skips the CP context
- Need Kimi K3 model architecture support
- [`distributed`] Use unit sharding for attention projections
- [`distributed`] Add expert-parallel token dispatch, default for Qwen3 MoE
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