Instructions to use MorcuendeA/MulderFinders with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MorcuendeA/MulderFinders with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MorcuendeA/MulderFinders", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MorcuendeA/MulderFinders", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("MorcuendeA/MulderFinders", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 1b74c856fc3e722738eaee5aff3d8743fe82de1867f90860d9e73849b40f895b
- Size of remote file:
- 2.58 MB
- SHA256:
- 9a232bd90edde7a90f2f1b6365667cae531fba456359bb58a9617b323e956339
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