Instructions to use joeldenny/complaint_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joeldenny/complaint_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joeldenny/complaint_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joeldenny/complaint_model") model = AutoModelForSequenceClassification.from_pretrained("joeldenny/complaint_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71bdf6c53a51a7fe1aa136d8f745890001d9564a69a71d36e1498794960b16e5
- Size of remote file:
- 3.58 kB
- SHA256:
- 3970539929dcebd08d0e416f9b2e26324ea5aeb51ee639583bf7ed538d941fe5
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