Feature Extraction
Transformers
Safetensors
deberta-v2
chemistry
bioinformatics
drug-discovery
text-embeddings-inference
Instructions to use SaeedLab/MolDeBERTa-small-123M-contrastive_mtr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/MolDeBERTa-small-123M-contrastive_mtr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/MolDeBERTa-small-123M-contrastive_mtr")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SaeedLab/MolDeBERTa-small-123M-contrastive_mtr") model = AutoModel.from_pretrained("SaeedLab/MolDeBERTa-small-123M-contrastive_mtr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a361e1485394538f17020e07115e8d5e1c46baafbb339cbe18e91917b89bfee
- Size of remote file:
- 84.1 MB
- SHA256:
- 4cb59038cc806d014efd22037b244880d92a6a04d5cf541abb7266574d9e953c
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