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:
- 6501545cbdbac735e76b0d4e03983ce5f7c97a49ef9748ff14e55c814e94318a
- Size of remote file:
- 1.42 GB
- SHA256:
- 5db803ee9652ac234917018ae4447f811f56649cc9401ab9b74b71fe5c5c7a63
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