Instructions to use Leslie123/stackoverflow-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Leslie123/stackoverflow-text-classification with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Leslie123/stackoverflow-text-classification") 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] - setfit
How to use Leslie123/stackoverflow-text-classification with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Leslie123/stackoverflow-text-classification") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Leslie123/stackoverflow-text-classification: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/Leslie123/stackoverflow-text-classification/resolve/refs%2Fpr%2F1/tokenizer_config.json
- Command line
-
hf download hf://Leslie123/stackoverflow-text-classification@refs/pr/1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Leslie123/stackoverflow-text-classification/resolve/refs%2Fpr%2F1/tokenizer_config.json
349 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "DistilBertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |