Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use BSC-NLP4BIA/BiomatDB-Substance-SetFit-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use BSC-NLP4BIA/BiomatDB-Substance-SetFit-Classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("BSC-NLP4BIA/BiomatDB-Substance-SetFit-Classifier") - sentence-transformers
How to use BSC-NLP4BIA/BiomatDB-Substance-SetFit-Classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BSC-NLP4BIA/BiomatDB-Substance-SetFit-Classifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |