Instructions to use akumar33/ManuBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akumar33/ManuBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="akumar33/ManuBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("akumar33/ManuBERT") model = AutoModelForMaskedLM.from_pretrained("akumar33/ManuBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c7be8eaab81ce7f049b4a6cfbb4312277584a5aae2ec4f869d1292588f7bdfb
- Size of remote file:
- 440 MB
- SHA256:
- a91af1d9077b403a5e781323717a057392c4e60e914a589486e9a2f25a488efb
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