Instructions to use ghadeermobasher/BioNLP13CG-Modified-scibert-uncased_latest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghadeermobasher/BioNLP13CG-Modified-scibert-uncased_latest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ghadeermobasher/BioNLP13CG-Modified-scibert-uncased_latest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ghadeermobasher/BioNLP13CG-Modified-scibert-uncased_latest") model = AutoModelForTokenClassification.from_pretrained("ghadeermobasher/BioNLP13CG-Modified-scibert-uncased_latest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, step 24000
ef1ae08 -
Training in progress, step 21500
0c8e603 -
Training in progress, step 19000
a2ce87c -
Training in progress, step 16500
2ffb7c1 -
Training in progress, step 13500
90f7ea3 -
Training in progress, step 10500
2097b0b -
Training in progress, step 8000
9063a2f -
Training in progress, step 5500
8971090 -
Training in progress, step 3000
9a2481e -
Training in progress, step 500
713c77a -
initial commit
00b7008