Text Classification
setfit
Safetensors
sentence-transformers
qwen3
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use fefofico/nuclear_trained_f2llm_temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use fefofico/nuclear_trained_f2llm_temp with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fefofico/nuclear_trained_f2llm_temp") - sentence-transformers
How to use fefofico/nuclear_trained_f2llm_temp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fefofico/nuclear_trained_f2llm_temp") 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
- Xet hash:
- 466fdb678c145d9341d3bf9550385cc46511385eeb0960872355b5678600c34e
- Size of remote file:
- 2.14 kB
- SHA256:
- 7a9e10c359bb2a0c130fbd4daf389f7d38ddd397379e1eba88d844535ed62e4b
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