Instructions to use gzquse/BioMethodModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gzquse/BioMethodModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gzquse/BioMethodModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gzquse/BioMethodModel") model = AutoModelForSequenceClassification.from_pretrained("gzquse/BioMethodModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ae87f09daf45fd78efa54f7442a15387d7956b8b67185c243e8a11baa77a885
- Size of remote file:
- 268 MB
- SHA256:
- 7f452db0f96a8fa8f7d0d42c018479f19ffbfb80e210b1b32dbc960fb3a6c6d3
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