Feature Extraction
Transformers
Safetensors
deberta-v2
chemistry
bioinformatics
drug-discovery
text-embeddings-inference
Instructions to use SaeedLab/MolDeBERTa-small-123M-mtr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/MolDeBERTa-small-123M-mtr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/MolDeBERTa-small-123M-mtr")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SaeedLab/MolDeBERTa-small-123M-mtr") model = AutoModel.from_pretrained("SaeedLab/MolDeBERTa-small-123M-mtr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e365c4c80537564539f1ee1bc42ce3ff6df76fd1bc12b0ac3d16d76a73905a6
- Size of remote file:
- 84.1 MB
- SHA256:
- 89f4cc8692e79e2bc49253b80b31a1ea746ceff8dc0d71090ecf0a701e04850b
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