Instructions to use mecoaoge2/ViHSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mecoaoge2/ViHSD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mecoaoge2/ViHSD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mecoaoge2/ViHSD") model = AutoModelForSequenceClassification.from_pretrained("mecoaoge2/ViHSD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3478e3cf3672e6c35a40f878f55638db57f12320952c33338133132ebc953b0e
- Size of remote file:
- 390 MB
- SHA256:
- 352d8f32b2508f0a02e40453f8d457f7ea1aced1ed7ab8db444b44bebbc97bdf
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