Instructions to use ThirdEyeData/Consumer-Complaint-Categorization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThirdEyeData/Consumer-Complaint-Categorization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThirdEyeData/Consumer-Complaint-Categorization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThirdEyeData/Consumer-Complaint-Categorization") model = AutoModelForSequenceClassification.from_pretrained("ThirdEyeData/Consumer-Complaint-Categorization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a901fe9b76dee0afb2632f17aa06b0b6c90d8a442e220551e9a6e9f8aed65c5a
- Size of remote file:
- 438 MB
- SHA256:
- 44c41e44017736a3c5af26f02e8df91e810447e6e7c2bd18c27ef6f0d720a837
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