Instructions to use TigerHatKth/xxx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TigerHatKth/xxx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TigerHatKth/xxx")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TigerHatKth/xxx") model = AutoModelForSequenceClassification.from_pretrained("TigerHatKth/xxx") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1225b9a1da92bd3756775457e8f82d0fedd2bfb609d9a28d012b77c72d8d8842
- Size of remote file:
- 4.54 kB
- SHA256:
- 447c636d40a7e8e6387d6629ef32810e27cf154b560415534a3a9e009a84cf9d
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