Instructions to use BrandonZYW/roberta-large-InBedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BrandonZYW/roberta-large-InBedder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BrandonZYW/roberta-large-InBedder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BrandonZYW/roberta-large-InBedder") model = AutoModelForMaskedLM.from_pretrained("BrandonZYW/roberta-large-InBedder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fa572d5be075c011c7c77f1810af79c334ec13c3ee7775003ab3a98268e792a
- Size of remote file:
- 4.66 kB
- SHA256:
- 696d0fabdedb7c0af5272af3d0c0666b382122081458f6323f75fa6731a0d01a
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