# Hugging Face Transformers v2.4.0 — Release & Upgrade Intelligence
- **Product:** Hugging Face Transformers (https://huggingface.co)
- **Version:** v2.4.0
- **Released:** Jan 31, 2020
- **Impact Score:** 7/10
- **Breaking Changes:** Source flagged
- **Canonical Analysis:** https://changelogs.us/transformers/updates/v2.4.0/

## Executive Summary (TL;DR)
Hugging Face Transformers v2.4.0. Source highlight: FlauBERT, MMBT, UmBERTo

## Breaking Changes & Deprecations
- [BREAKING CHANGES] ## Ignored indices in PyTorch loss computing (@LysandreJik)

## New Features
- MMBT was added to the list of available models, as the first multi-modal model to make it in the library. It can accept a transformer model as well as a computer vision model, in order to classify image and text. The MMBT Model is from Supervised Multimodal Bitransformers for Classifying Images and Text by Douwe Kiela, Suvrat Bhooshan, Hamed Firooz, Davide Testuggine (https://github.com/facebookresearch/mmbt/)
- A new Dutch BERT model was added under the `wietsedv/bert-base-dutch-cased` identifier. Added by @wietsedv. **Model page**
- A new French model was added, FlauBERT, based on XLM. The FlauBERT model is from FlauBERT: Unsupervised Language Model Pre-training for French (https://github.com/getalp/Flaubert). Four checkpoints are added: small size, base uncased, base cased and large. **Model page**
- TensorFlow XLM-RoBERTa was added (@jplu )
- TensorFlow CamemBERT was added (@jplu )
- Greatly improved the quality of the source code by leveraging `black`, `isort` and `flake8`. A test was added, `check_code_quality`, which checks that the contributions respect the contribution guidelines related to those tools.

## Bug Fixes
- Fixed the environment variables so that they don't fight each other anymore (USE_TF, USE_TORCH)
- Can now save and load PreTrainedEncoderDecoder objects (@TheEdoardo93)
- RoBERTa now bears more similarity to the FairSeq implementation (@DomHudson, @thomwolf)
- Examples now better reflect the defaults of the encoding methods (@enzoampil)
- TFXLNet now  has a correct input mask (@thomwolf)
- run_squad was fixed to allow better training for XLNet (@importpandas )

## Upgrade Command
```bash
python -m pip install 'transformers==2.4.0'
```