Instructions to use kunxiaogao/New_BioRED_model_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kunxiaogao/New_BioRED_model_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kunxiaogao/New_BioRED_model_1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kunxiaogao/New_BioRED_model_1") model = AutoModelForTokenClassification.from_pretrained("kunxiaogao/New_BioRED_model_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 605bdd22bd26d0e254597b574295653499df39709a34e0338fa516f6484c17fa
- Size of remote file:
- 3.44 kB
- SHA256:
- 27502947dbfd7d1403905387909575d412fdf1fffc17192e941a4c145bda7ac0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.