Instructions to use utter-project/hutter-12-3rd-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Fairseq
How to use utter-project/hutter-12-3rd-base with Fairseq:
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub models, cfg, task = load_model_ensemble_and_task_from_hf_hub( "utter-project/hutter-12-3rd-base" ) - Notebooks
- Google Colab
- Kaggle
| license: cc-by-nc-4.0 | |
| datasets: | |
| - mozilla-foundation/common_voice_11_0 | |
| language: | |
| - fr | |
| - es | |
| - pt | |
| - da | |
| - de | |
| - nl | |
| - fy | |
| - zh | |
| - ja | |
| - ar | |
| - sw | |
| - gn | |
| library_name: fairseq | |
| **HUTTER-12: H(uBERT) UTTER model covering 12 languages.** | |
| * Total training hours: 1,622 from Romance (French: 300h, Spanish: 300h, Portuguese: 102.3h), West-Germanic (Danish: 3.5h, German: 300h, Dutch: 72.1h, Frisian: 41.2h) and other languages (Chinese (zh-CN): 104.6h, Japanese: 37h, Arabic: 61h, Swahili 300h, Guaraní: 0.4h) | |
| * Number of updates: 400K | |
| * Number of iterations: 3 | |
| * Clustering approach: mini-batch K-means (100% of the data) | |
| * Dataset: CommonVoice v13 | |
| # Funding | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/62262e19d36494a6f743a28d/HbzC1C-uHe25ewTy2wyoK.png" width=7% height=7%> | |
| This is an output of the European Project UTTER (Unified Transcription and Translation for Extended Reality) under grant number 101070631. For more information go to https://he-utter.eu/ | |