Instructions to use demdecuong/stroke_sup_simcse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use demdecuong/stroke_sup_simcse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="demdecuong/stroke_sup_simcse")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("demdecuong/stroke_sup_simcse") model = AutoModel.from_pretrained("demdecuong/stroke_sup_simcse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from demdecuong/stroke_sup_simcse: direct link, hf CLI and curl.
- Browser
- Download file 523 Bytes
-
https://huggingface.co/demdecuong/stroke_sup_simcse/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://demdecuong/stroke_sup_simcse/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/demdecuong/stroke_sup_simcse/resolve/main/tokenizer_config.json
523 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "name_or_path": "princeton-nlp/sup-simcse-bert-base-uncased", "special_tokens_map_file": "/root/.cache/huggingface/transformers/8c406286308d13c3a53bc10c3d1a2d5113d4e46a34cb6ec5ee06e5d9762c462c.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "do_basic_tokenize": true, "never_split": null} |