Instructions to use m3hrdadfi/rag-token-multiset-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/rag-token-multiset-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RagTokenForGeneration tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/rag-token-multiset-base") model = RagTokenForGeneration.from_pretrained("m3hrdadfi/rag-token-multiset-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download question_encoder_tokenizer/tokenizer_config.json from m3hrdadfi/rag-token-multiset-base: direct link, hf CLI and curl.
- Browser
- Download file 328 Bytes
-
https://huggingface.co/m3hrdadfi/rag-token-multiset-base/resolve/main/question_encoder_tokenizer/tokenizer_config.json
- Command line
-
hf download hf://m3hrdadfi/rag-token-multiset-base/question_encoder_tokenizer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/m3hrdadfi/rag-token-multiset-base/resolve/main/question_encoder_tokenizer/tokenizer_config.json
328 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "DPRQuestionEncoderTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |