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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c68ea580f327fbdd32f1e9e9a697e3109d512f3102040cd95a0f17d908697eb
- Size of remote file:
- 268 MB
- SHA256:
- 62d148d563948bb17e3021f69e620abd473eb6f5eddcd3f312ed1c7f8d74bcb5
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