Instructions to use mp6kv/feedback_intent_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mp6kv/feedback_intent_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mp6kv/feedback_intent_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mp6kv/feedback_intent_test") model = AutoModelForSequenceClassification.from_pretrained("mp6kv/feedback_intent_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4a0e21bf357051ec846ad19bba27655d5ea13b22360483ae0397b6fe57fd453
- Size of remote file:
- 499 MB
- SHA256:
- 0214f73fa92a00800eff6758294409b23dcd540d21de823869d4407e47ff27fb
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