Instructions to use Yanhao/simcse-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yanhao/simcse-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Yanhao/simcse-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Yanhao/simcse-roberta-large") model = AutoModel.from_pretrained("Yanhao/simcse-roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Yanhao/simcse-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 253 Bytes
-
https://huggingface.co/Yanhao/simcse-roberta-large/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Yanhao/simcse-roberta-large/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/Yanhao/simcse-roberta-large/resolve/main/tokenizer_config.json
253 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": "bert-large-uncased"} |