Text Classification
setfit
Safetensors
sentence-transformers
qwen3
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use fefofico/nuclear_trained_f2llm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use fefofico/nuclear_trained_f2llm with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fefofico/nuclear_trained_f2llm") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use fefofico/nuclear_trained_f2llm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fefofico/nuclear_trained_f2llm") 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
Download model.safetensors from fefofico/nuclear_trained_f2llm: direct link, hf CLI and curl.
- Browser
- Download file 320 MB
-
https://huggingface.co/fefofico/nuclear_trained_f2llm/resolve/main/model.safetensors
- Command line
-
hf download hf://fefofico/nuclear_trained_f2llm/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/fefofico/nuclear_trained_f2llm/resolve/main/model.safetensors
320 MB
- Xet hash:
- b31597aa7c3d7674b5cbb9bb9f150db85fd3f7b5de44000e561c7b494b820263
- Size of remote file:
- 320 MB
- SHA256:
- 808f692da946f4e66300279aa240099655cebf2ff6c268e825d623ba2da7263e
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