Instructions to use RAYZ/openqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RAYZ/openqa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RagSequenceForGeneration tokenizer = AutoTokenizer.from_pretrained("RAYZ/openqa") model = RagSequenceForGeneration.from_pretrained("RAYZ/openqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download question_encoder_tokenizer/tokenizer_config.json from RAYZ/openqa: direct link, hf CLI and curl.
- Browser
- Download file 498 Bytes
-
https://huggingface.co/RAYZ/openqa/resolve/main/question_encoder_tokenizer/tokenizer_config.json
- Command line
-
hf download hf://RAYZ/openqa/question_encoder_tokenizer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/RAYZ/openqa/resolve/main/question_encoder_tokenizer/tokenizer_config.json
498 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "name_or_path": "hfl/chinese-macbert-base", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": "/home/rayz/.cache/huggingface/transformers/9f382d012cf0761684535742ec8cf1096e0be52359ee0389a418eaada1265367.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |