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:
- 5c7b08ed88b642ee42323256b886862ef2dd1f4efc0f9c65682c0ee0fd2526ca
- Size of remote file:
- 849 MB
- SHA256:
- 9c6d569960e50f952ac73dc824edee37878799713de4fee344cbc575b741918e
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