Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use ThomBors/NLBSE2026-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use ThomBors/NLBSE2026-python with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ThomBors/NLBSE2026-python") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use ThomBors/NLBSE2026-python with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ThomBors/NLBSE2026-python") 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 checkpoint-178970/training_args.bin from ThomBors/NLBSE2026-python: direct link, hf CLI and curl.
- Browser
- Download file 6.1 kB
-
https://huggingface.co/ThomBors/NLBSE2026-python/resolve/main/checkpoint-178970/training_args.bin
- Command line
-
hf download hf://ThomBors/NLBSE2026-python/checkpoint-178970/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ThomBors/NLBSE2026-python/resolve/main/checkpoint-178970/training_args.bin
6.1 kB
- Xet hash:
- 3674f0abae0c6c5f0172e0ccc56ce4829a3b6a5654e4ec154485df6d77d48d6d
- Size of remote file:
- 6.1 kB
- SHA256:
- 9867dbc8259d4f7e5c213a94434aab9e2e02a71eb843fafdb7089281ef1c89ce
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