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:
- 98827e9a0119b19c2ee72121d0a516556c4eab12443e216d54bbf3da1d742d69
- Size of remote file:
- 438 MB
- SHA256:
- 3861c876540914d50a466dfc8824fa8b33b7268190b8e24652727a4f9ce30c12
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