Text Classification
setfit
Safetensors
sentence-transformers
qwen3
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use fefofico/crisis_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use fefofico/crisis_trained with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fefofico/crisis_trained") - sentence-transformers
How to use fefofico/crisis_trained with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fefofico/crisis_trained") 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
| { | |
| "prompts": { | |
| "web_search_query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery: ", | |
| "sts_query": "Instruct: Retrieve semantically similar text\nQuery: ", | |
| "bitext_query": "Instruct: Retrieve parallel sentences\nQuery: " | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine", | |
| "__version__": { | |
| "sentence_transformers": "3.4.1", | |
| "transformers": "4.57.6", | |
| "pytorch": "2.10.0+cu128" | |
| } | |
| } |