Instructions to use ghadeermobasher/BioNLP13-Modified-BioBERT-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghadeermobasher/BioNLP13-Modified-BioBERT-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ghadeermobasher/BioNLP13-Modified-BioBERT-512")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ghadeermobasher/BioNLP13-Modified-BioBERT-512") model = AutoModelForTokenClassification.from_pretrained("ghadeermobasher/BioNLP13-Modified-BioBERT-512", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ghadeermobasher/BioNLP13-Modified-BioBERT-512: direct link, hf CLI and curl.
- Browser
- Download file 613 Bytes
-
https://huggingface.co/ghadeermobasher/BioNLP13-Modified-BioBERT-512/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ghadeermobasher/BioNLP13-Modified-BioBERT-512/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/ghadeermobasher/BioNLP13-Modified-BioBERT-512/resolve/main/tokenizer_config.json
613 Bytes
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "problem_type": "multi_label_classification", "max_length": 512, "special_tokens_map_file": "/home/mobashgr/.cache/huggingface/transformers/118da8438a7854000cfcf052566f83ae4f4159ac25796e49e16c3b18746041b4.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "dmis-lab/biobert-v1.1", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |