Instructions to use microsoft/DialogRPT-width with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/DialogRPT-width with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/DialogRPT-width")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/DialogRPT-width") model = AutoModelForSequenceClassification.from_pretrained("microsoft/DialogRPT-width", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/DialogRPT-width: direct link, hf CLI and curl.
- Browser
- Download file 1.52 GB
-
https://huggingface.co/microsoft/DialogRPT-width/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/DialogRPT-width/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/DialogRPT-width/resolve/main/pytorch_model.bin
1.52 GB
- Xet hash:
- 6e6f9e61768cfccf0aa38512044e46ef299edb097310fd34ee6a3741532977f3
- Size of remote file:
- 1.52 GB
- SHA256:
- ec5c1ad33b1e38c22d33ddd455b6202c112aa85a169fa2f9307ce1fbb759fb6f
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