Instructions to use moussaKam/mbarthez with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/mbarthez with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="moussaKam/mbarthez")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("moussaKam/mbarthez") model = AutoModelForSeq2SeqLM.from_pretrained("moussaKam/mbarthez", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14db2d4ea3313ff8981fc7d1cb4b00d8566154263029856babc5cf35bf5c333e
- Size of remote file:
- 1.83 GB
- SHA256:
- d31646709f3790d6c54cf534ceb94d69358709a543c47be04d47ce23289e6648
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