Text Classification
setfit
Safetensors
sentence-transformers
English
bert
sentiment-analysis
few-shot-learning
Eval Results (legacy)
text-embeddings-inference
Instructions to use loganh274/nlp-testing-setfit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use loganh274/nlp-testing-setfit with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("loganh274/nlp-testing-setfit") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use loganh274/nlp-testing-setfit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("loganh274/nlp-testing-setfit") 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_metadata.json from loganh274/nlp-testing-setfit: direct link, hf CLI and curl.
- Browser
- Download file 1.28 kB
-
https://huggingface.co/loganh274/nlp-testing-setfit/resolve/main/model_metadata.json
- Command line
-
hf download hf://loganh274/nlp-testing-setfit/model_metadata.json
-
curl -L -o model_metadata.json https://huggingface.co/loganh274/nlp-testing-setfit/resolve/main/model_metadata.json
1.28 kB
| { | |
| "labels": [ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4 | |
| ], | |
| "num_labels": 5, | |
| "environment": { | |
| "python": "3.11.14 (main, Oct 9 2025, 16:16:55) [Clang 17.0.0 (clang-1700.4.4.1)]", | |
| "scikit-learn": "1.8.0", | |
| "setfit": "1.1.3", | |
| "torch": "2.9.1" | |
| }, | |
| "base_model": "BAAI/bge-base-en-v1.5", | |
| "serialization": "safetensors", | |
| "training_config": { | |
| "batch_size": 16, | |
| "num_epochs": [ | |
| 1, | |
| 16 | |
| ], | |
| "training_samples": 540, | |
| "test_samples": 100 | |
| }, | |
| "model_stats": { | |
| "total_parameters": 109482240, | |
| "trainable_parameters": 109482240, | |
| "body_parameters": 109482240, | |
| "head_parameters": 0, | |
| "model_size_mb": 417.64, | |
| "model_description": "SetFit model with 109,482,240 total parameters (417.6 MB)" | |
| }, | |
| "evaluation_metrics": { | |
| "accuracy": 0.88, | |
| "f1_weighted": 0.8805050505050506, | |
| "f1_macro": 0.8805050505050506, | |
| "precision_weighted": 0.8883333333333333, | |
| "precision_macro": 0.8883333333333333, | |
| "recall_weighted": 0.88, | |
| "recall_macro": 0.8799999999999999 | |
| }, | |
| "training_summary": { | |
| "epochs_trained": 5, | |
| "final_loss": 0.0893 | |
| } | |
| } |