Instructions to use i-dhilip/intent_predict_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use i-dhilip/intent_predict_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="i-dhilip/intent_predict_train")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("i-dhilip/intent_predict_train") model = AutoModelForSequenceClassification.from_pretrained("i-dhilip/intent_predict_train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c580b305499a7dc40b33feb695788571484b3521948ac12bb10640d3b3799041
- Size of remote file:
- 268 MB
- SHA256:
- bd05686e217af58e5dcd99efdd3cf7e92b19f2ed9a348b3e526d9f749a74c3fd
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