Instructions to use nguyenvulebinh/envibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nguyenvulebinh/envibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nguyenvulebinh/envibert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nguyenvulebinh/envibert") model = AutoModelForMaskedLM.from_pretrained("nguyenvulebinh/envibert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4012a447d8e9ec4c6b968bd9196f2e4cfe6bd3d80871637624d3cc070f3d44bb
- Size of remote file:
- 283 MB
- SHA256:
- 1f497425b7753cda40fbd04627c79c7407577a0751934271c10f61092fd32f37
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