Instructions to use nadika/grievance_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nadika/grievance_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nadika/grievance_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nadika/grievance_classification") model = AutoModelForSequenceClassification.from_pretrained("nadika/grievance_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 423b60a511a77b7e6b8d0cd15de89899226b0d76fd902da83e62ca0f99c2c301
- Size of remote file:
- 4.86 kB
- SHA256:
- 6f532a2e693f65caf66b946b4bf91b2209ce18a144be4fc8cc2c43e82ad26aa3
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