# Hugging Face Transformers v4.11.0 — Release & Upgrade Intelligence
- **Product:** Hugging Face Transformers (https://huggingface.co)
- **Version:** v4.11.0
- **Released:** Sep 27, 2021
- **Impact Score:** 7/10
- **Breaking Changes:** Source flagged
- **Canonical Analysis:** https://changelogs.us/transformers/updates/v4.11.0/

## Executive Summary (TL;DR)
Hugging Face Transformers v4.11.0. Source highlight: v4.11.0: GPT-J, Speech2Text2, FNet, Pipeline GPU utilization, dynamic model code loading

## Breaking Changes & Deprecations
- Breaking changes *We strive for no breaking changes between releases - however, some bugs are not discovered for long periods of time, and users may eventually rely on such bugs. We document here such changes that may affect users when updating to a recent version.*

## New Features
- Add SpeechEncoderDecoder & Speech2Text2 #13186 (@patrickvonplaten)
- Add FNet #13045 (@gchhablani)
- Add the `AudioClassificationPipeline` #13342 (@anton-l)
- Add SigOpt HPO to transformers trainer api #13572 (@kding1)
- Add cpu distributed fine-tuning support for transformers Trainer API #13574 (@kding1)

## Improvements
- Users should notice much fewer unnecessary warnings and less 'console spam' in general while using Transformers with TensorFlow.
- TensorFlow models should be less picky about the specific integer dtypes (int32/int64) that are passed as input
- You can now compile our TensorFlow models without passing a loss argument! If you do, the model will compute loss internally during the forward pass and then use this value to fit() on. This makes it much more convenient to get the right loss, particularly since many models have unique losses for certain tasks that are easy to overlook and annoying to reimplement. Remember to pass your labels as the "labels" key of your input dict when doing this, so that they're accessible to the model during t
- Modified TF train_step #13678 (@Rocketknight1)
- Removed console spam from misfiring warnings #13625 (@Rocketknight1)

## Bug Fixes
- Fix Tensorflow T5 with int64 input #13479 (@Rocketknight1)
- MarianMT int dtype fix #13496 (@Rocketknight1)
- [Wav2Vec2] Fix normalization for non-padded tensors #13512 (@patrickvonplaten)
- Fixes for the documentation #13361 (@sgugger)
- fix wrong 'cls' masking for bigbird qa model output #13143 (@donggyukimc)
- Improve T5 docs #13240 (@NielsRogge)

## Upgrade Command
```bash
python -m pip install 'transformers==4.11.0'
```