Text Classification
Transformers
PyTorch
Safetensors
bert
chemistry
biology
drug-discovery
drug-target
chembl34
selfies
drugs
molecules
compounds
Eval Results (legacy)
text-embeddings-inference
Instructions to use gbyuvd/drugtargetpred-chemselfies with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gbyuvd/drugtargetpred-chemselfies with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gbyuvd/drugtargetpred-chemselfies")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gbyuvd/drugtargetpred-chemselfies") model = AutoModelForSequenceClassification.from_pretrained("gbyuvd/drugtargetpred-chemselfies") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe5b1f553417ba93b0756f753e9034dfa68915a2a0f028aca61c656ef2360403
- Size of remote file:
- 44.8 MB
- SHA256:
- 5c338782ea04774723c0a0775199b28a0ffb9d947273047d65be7664e2b7ad49
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