Text Classification
setfit
PyTorch
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use pacoreyes/StanceFit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use pacoreyes/StanceFit with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("pacoreyes/StanceFit") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use pacoreyes/StanceFit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pacoreyes/StanceFit") 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 tokenizer_config.json from pacoreyes/StanceFit: direct link, hf CLI and curl.
- Browser
- Download file 396 Bytes
-
https://huggingface.co/pacoreyes/StanceFit/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://pacoreyes/StanceFit/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/pacoreyes/StanceFit/resolve/main/tokenizer_config.json
396 Bytes
| { | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "do_lower_case": true, | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "name_or_path": "checkpoints/step_2000/", | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "special_tokens_map_file": null, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "MPNetTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |