Instructions to use jonghyunlee/ChemBERT_ChEMBL_pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonghyunlee/ChemBERT_ChEMBL_pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jonghyunlee/ChemBERT_ChEMBL_pretrained")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jonghyunlee/ChemBERT_ChEMBL_pretrained") model = AutoModel.from_pretrained("jonghyunlee/ChemBERT_ChEMBL_pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 3c47826
Update README.md
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README.md
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@@ -14,7 +14,7 @@ The model architecture utilized is based on BERT. Here are the key configuration
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```
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BertConfig(
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vocab_size=
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hidden_size=256,
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num_hidden_layers=8,
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num_attention_heads=8,
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```
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BertConfig(
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vocab_size=70,
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hidden_size=256,
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num_hidden_layers=8,
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num_attention_heads=8,
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