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:
- 69edf6ae386322bdd3b96222187f7d9d77ce309e9560234d15ce927e0343dd9e
- Size of remote file:
- 3.39 kB
- SHA256:
- 7e0c3dd372a7733392299509b17ac617056c7f6a531848de791f769254d9f656
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