Instructions to use qud-parsing/compatibility_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qud-parsing/compatibility_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="qud-parsing/compatibility_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("qud-parsing/compatibility_model") model = AutoModelForSequenceClassification.from_pretrained("qud-parsing/compatibility_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 584cdf3e77fec955686d08a585b1fe352873b68d0721085bded471f447930c31
- Size of remote file:
- 1.71 kB
- SHA256:
- 98d224803526afb65f31b0849d3c380c5b8b23fbbd5cdae8ced87d6ff5d88193
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