Instructions to use dell-research-harvard/byline-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dell-research-harvard/byline-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dell-research-harvard/byline-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dell-research-harvard/byline-detection") model = AutoModelForTokenClassification.from_pretrained("dell-research-harvard/byline-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from dell-research-harvard/byline-detection: direct link, hf CLI and curl.
- Browser
- Download file 373 Bytes
-
https://huggingface.co/dell-research-harvard/byline-detection/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://dell-research-harvard/byline-detection/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/dell-research-harvard/byline-detection/resolve/main/tokenizer_config.json
373 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "DistilBertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |