Instructions to use arjunth2001/priv_ftc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arjunth2001/priv_ftc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="arjunth2001/priv_ftc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("arjunth2001/priv_ftc") model = AutoModelForSequenceClassification.from_pretrained("arjunth2001/priv_ftc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f186c0865deebe66d994c731be7c5af3cb055e9150a02fc96ea1e9cac8e4ac6
- Size of remote file:
- 438 MB
- SHA256:
- dd73fc4a83f94bc7dd407bf85e6defda00efce280ce8f0ecad33a6893ded6d1d
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