Text Classification
setfit
Safetensors
sentence-transformers
new
generated_from_setfit_trainer
custom_code
text-embeddings-inference
Instructions to use tmp-org/tmp_cv_model_2025_09_29_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use tmp-org/tmp_cv_model_2025_09_29_0 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("tmp-org/tmp_cv_model_2025_09_29_0") - sentence-transformers
How to use tmp-org/tmp_cv_model_2025_09_29_0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tmp-org/tmp_cv_model_2025_09_29_0", trust_remote_code=True) 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
| { | |
| "labels": [ | |
| "Einkaufsliste_Einkaufsliste", | |
| "Kasse_Aktivierte Coupons", | |
| "Kasse_Kasse", | |
| "Kasse_Loading", | |
| "Kasse_Mobil bezahlen", | |
| "Kasse_Unknown", | |
| "Other_Code einl\u00f6sen", | |
| "Other_Coupon details", | |
| "Other_Kassenbons", | |
| "Other_Loading", | |
| "Other_Marktsuche", | |
| "Other_Menu", | |
| "Other_Neuigkeiten", | |
| "Other_Other", | |
| "Other_Produktherkunft", | |
| "Other_Prospekt", | |
| "Other_Treueaktionen", | |
| "Other_Unknown", | |
| "Pr\u00e4mien_Pr\u00e4mien", | |
| "Sparen_Angebote", | |
| "Sparen_Coupons", | |
| "Sparen_Loading", | |
| "Start_Loading", | |
| "Start_Start" | |
| ], | |
| "normalize_embeddings": false | |
| } |