Instructions to use BDRC/Bo-Multilayer-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BDRC/Bo-Multilayer-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BDRC/Bo-Multilayer-Detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BDRC/Bo-Multilayer-Detection") model = AutoModelForTokenClassification.from_pretrained("BDRC/Bo-Multilayer-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from BDRC/Bo-Multilayer-Detection: direct link, hf CLI and curl.
- Browser
- Download file 574 Bytes
-
https://huggingface.co/BDRC/Bo-Multilayer-Detection/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://BDRC/Bo-Multilayer-Detection/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/BDRC/Bo-Multilayer-Detection/resolve/main/tokenizer_config.json
574 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<bos>", | |
| "clean_up_tokenization_spaces": false, | |
| "cls_token": "<bos>", | |
| "eos_token": "<eos>", | |
| "extra_special_tokens": [ | |
| "<start_of_turn>", | |
| "<end_of_turn>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 8192, | |
| "pad_token": "<pad>", | |
| "padding_side": "right", | |
| "sep_token": "<eos>", | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>" | |
| } | |