Instructions to use StevenZHB/Bio-Inject-Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StevenZHB/Bio-Inject-Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="StevenZHB/Bio-Inject-Bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("StevenZHB/Bio-Inject-Bert") model = AutoModelForMaskedLM.from_pretrained("StevenZHB/Bio-Inject-Bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39d0ec82f1c50b2874dd2c2d1fe2c4fe51a40f4657e1a381c93907fed1249fd3
- Size of remote file:
- 438 MB
- SHA256:
- 23d67f885bd6d14ada24620dcbb5411c4e1ab740d12c419ec0d3c8c02de9a6bd
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