Instructions to use CWrecker/BIOBert-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CWrecker/BIOBert-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CWrecker/BIOBert-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CWrecker/BIOBert-Classification") model = AutoModelForSequenceClassification.from_pretrained("CWrecker/BIOBert-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 043ea9a61f1670a4d81bd5a2c0cdf8ff112bfa802392dc2cb34778c989f2a23a
- Size of remote file:
- 433 MB
- SHA256:
- 13e2352bd039f3fa4e82ccfcbc3a9fb484361f0c0cfe184e9fb9823934e0ab0b
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