Instructions to use iamdanialkamali/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamdanialkamali/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iamdanialkamali/output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iamdanialkamali/output") model = AutoModelForSequenceClassification.from_pretrained("iamdanialkamali/output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a60c8fbdace85fccc0c314593244688e1aed7256a2986711bed0d85f36c4abbb
- Size of remote file:
- 4.73 kB
- SHA256:
- 6b2dc8076dced952167e1c753f8cc01fcd5178c143957a6c8faafc27d2b09bd8
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