Instructions to use MilosKosRad/BioNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MilosKosRad/BioNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MilosKosRad/BioNER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MilosKosRad/BioNER") model = AutoModelForTokenClassification.from_pretrained("MilosKosRad/BioNER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 690ca3ffab36ffaab18f7251947628b003442a6d15f536e91ba63a6626d39175
- Size of remote file:
- 436 MB
- SHA256:
- 9aafe933695aa30c57dd815ac4084470fd4d166026ae7085fc6c87d0e9ff485a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.