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:
- 8ae380eeeea1c55f3126d82d258b5794cee8473f8cf64e52a705e6b4fe30cdc3
- Size of remote file:
- 2.99 kB
- SHA256:
- 1aed674ba2de162e397fd952e529b1205901fbc8339183090e2972d717dc7c0e
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