Instructions to use gumgo91/IUPAC_BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gumgo91/IUPAC_BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="gumgo91/IUPAC_BERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gumgo91/IUPAC_BERT") model = AutoModel.from_pretrained("gumgo91/IUPAC_BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 889a91c87fe0f847e04a138a55a52f7fdabb952c2a73c431f42b70a7bdc6e5e6
- Size of remote file:
- 349 MB
- SHA256:
- 167dbd84527d4647c7cc413c919433c7ac92fbfc433c0ffefe46d853388a3261
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