Instructions to use nmcahill/TJ-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmcahill/TJ-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nmcahill/TJ-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nmcahill/TJ-classifier") model = AutoModelForSequenceClassification.from_pretrained("nmcahill/TJ-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08d5cc5d984c41e3c2471b039e82c628f31cf96c5e5060750674e7f77350f29f
- Size of remote file:
- 268 MB
- SHA256:
- 21a08203219f2f9c7cbdb0e9b0cbb79eaeba55b6034e299d8e895f77f8390500
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