Instructions to use IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese") model = AutoModelForSequenceClassification.from_pretrained("IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese/special_tokens_map.json
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curl -L -o special_tokens_map.json https://huggingface.co/IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese/resolve/main/special_tokens_map.json
112 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |