Instructions to use IssamL/pv-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IssamL/pv-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IssamL/pv-class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IssamL/pv-class") model = AutoModelForSequenceClassification.from_pretrained("IssamL/pv-class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45caafc06150e6583f4a7867d4d0aa2953afb446b8b3f9c0bcecacec420b1303
- Size of remote file:
- 4.03 kB
- SHA256:
- 96de014eff3276ee404148dc0743a3c6bbb3d61060a2b48f2f5094eb39defa84
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