Instructions to use 29m10/distilbert-base-uncased-finetuned-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 29m10/distilbert-base-uncased-finetuned-intent with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased") model = PeftModel.from_pretrained(base_model, "29m10/distilbert-base-uncased-finetuned-intent") - Transformers
How to use 29m10/distilbert-base-uncased-finetuned-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="29m10/distilbert-base-uncased-finetuned-intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("29m10/distilbert-base-uncased-finetuned-intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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