Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ITOCJ/SciGenSetfit2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use ITOCJ/SciGenSetfit2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ITOCJ/SciGenSetfit2") - sentence-transformers
How to use ITOCJ/SciGenSetfit2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ITOCJ/SciGenSetfit2") 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
| { | |
| "normalize_embeddings": false, | |
| "labels": [ | |
| "Aims", | |
| "Background", | |
| "Hypothesis", | |
| "Implications", | |
| "Importance", | |
| "Limitations", | |
| "Method", | |
| "None", | |
| "Purpose", | |
| "Reccomendations", | |
| "Result", | |
| "Uncertainty" | |
| ] | |
| } |