Instructions to use yujuyeon/SciLinkBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yujuyeon/SciLinkBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="yujuyeon/SciLinkBERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("yujuyeon/SciLinkBERT") model = AutoModel.from_pretrained("yujuyeon/SciLinkBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 596302c7dd7982c1dcf16854a31318b804e3137ee7ef03d00a06abe4d0399224
- Size of remote file:
- 433 MB
- SHA256:
- 6075130d7a1e43337d2ad9a6edc979c1d28c40224380c9dcbaad6ccfa055a2a6
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