Instructions to use simonlevine/biomed_roberta_base-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonlevine/biomed_roberta_base-4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonlevine/biomed_roberta_base-4096")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonlevine/biomed_roberta_base-4096") model = AutoModelForMaskedLM.from_pretrained("simonlevine/biomed_roberta_base-4096") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a035ab6c7d5dc9c93ade3345b1e29a765b2d5952b382c32cc7f7cdd72d1a8fd1
- Size of remote file:
- 510 MB
- SHA256:
- 97c93e91460ed4a40847e85cdffd059f53bfe446ed1603a0f46c983cb6410036
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