Instructions to use nepp1d0/Bert-pretrained-smilesBindingDB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nepp1d0/Bert-pretrained-smilesBindingDB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nepp1d0/Bert-pretrained-smilesBindingDB")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nepp1d0/Bert-pretrained-smilesBindingDB") model = AutoModelForMaskedLM.from_pretrained("nepp1d0/Bert-pretrained-smilesBindingDB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d1b32e5c3a9c89c8678e1ebedca335a7c127b33f08ca040797a79f5ffe52c29
- Size of remote file:
- 174 MB
- SHA256:
- e4952ac91d5dbc4cdc4f14bc0f498c8bd9b208ac1df6178f816520c60a727011
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