Instructions to use microsoft/DialogRPT-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/DialogRPT-depth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/DialogRPT-depth")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/DialogRPT-depth") model = AutoModelForSequenceClassification.from_pretrained("microsoft/DialogRPT-depth") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33c340a0c9a273c3c52b4fa3980fb062cf9bc744ba098e138e3fefd7f938108f
- Size of remote file:
- 1.52 GB
- SHA256:
- 5c177b91a84c6e0215b02dd651d14e4da7e6021fb3762e1f06c8b985104908d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.