Instructions to use crcb/hs_dvs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crcb/hs_dvs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="crcb/hs_dvs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("crcb/hs_dvs") model = AutoModelForSequenceClassification.from_pretrained("crcb/hs_dvs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad1560edb153b66bf32fe0182ce17f0354b4802478f4838284945e63619dff08
- Size of remote file:
- 263 MB
- SHA256:
- f765eedc0ab0e54770ff6b1fda54fb99d5faeac0f31e696506688b87527dc946
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