Instructions to use SALT-NLP/FLANG-DistilBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SALT-NLP/FLANG-DistilBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SALT-NLP/FLANG-DistilBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SALT-NLP/FLANG-DistilBERT") model = AutoModelForMaskedLM.from_pretrained("SALT-NLP/FLANG-DistilBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba594963664dbf5e21a9906089727866b20c93b3b3deac3e357d4fc6c971e7e0
- Size of remote file:
- 268 MB
- SHA256:
- cc69a7e40b94fcf6e85d31dc0d78e650bd791d01f309a308953fae3e2fd1a772
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