Instructions to use TigerHatKth/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TigerHatKth/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TigerHatKth/content")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TigerHatKth/content") model = AutoModelForSequenceClassification.from_pretrained("TigerHatKth/content") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5b23284fbcc2953a7f06256414f61bf457aa2b1746e2b4457aec1da05cadd4d
- Size of remote file:
- 4.54 kB
- SHA256:
- 8665a6153f697566afd4138abe82ebde9bae158d4e1a064559fa29523df5029c
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