Fill-Mask
Transformers
Safetensors
modchembert
modernbert
ModChemBERT
cheminformatics
chemical-language-model
molecular-property-prediction
mergekit
Merge
custom_code
Eval Results (legacy)
Instructions to use Derify/ModChemBERT-MLM-TAFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Derify/ModChemBERT-MLM-TAFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Derify/ModChemBERT-MLM-TAFT", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Derify/ModChemBERT-MLM-TAFT", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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Install the `transformers` library starting from v4.56.1:
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```bash
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pip install -U transformers>=4.56.1
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```
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### Load Model
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Install the `transformers` library starting from v4.56.1:
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```bash
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pip install -U "transformers>=4.56.1,<5.0.0"
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```
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### Load Model
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