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:
- 427f5f4f0250d6e5927cbf8d765875c2c9ec3c0589c3c30e6f420edd336e56e4
- Size of remote file:
- 849 MB
- SHA256:
- 57ebd62773f7092cfe0f5bb70bd3d2e849fab7643ab713b10a74dd2799e37f1b
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