Instructions to use allenai/vila-scibert-cased-s2vl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/vila-scibert-cased-s2vl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="allenai/vila-scibert-cased-s2vl")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("allenai/vila-scibert-cased-s2vl") model = AutoModelForTokenClassification.from_pretrained("allenai/vila-scibert-cased-s2vl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 138ccc9a55748157f87aa511006e23e9cd5019d5c65095fead0f757b28ff4a68
- Size of remote file:
- 438 MB
- SHA256:
- f1c2a7a8904d6a68c1d794f9a1338a5dc5f3cdafd80bd1ab49a11276c8e161ac
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