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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/DialogRPT-depth: direct link, hf CLI and curl.
- Browser
- Download file 1.52 GB
-
https://huggingface.co/microsoft/DialogRPT-depth/resolve/68ff13b00a668b64e117373ad0f08d26f130f704/pytorch_model.bin
- Command line
-
hf download hf://microsoft/DialogRPT-depth@68ff13b00a668b64e117373ad0f08d26f130f704/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/DialogRPT-depth/resolve/68ff13b00a668b64e117373ad0f08d26f130f704/pytorch_model.bin
1.52 GB
- Xet hash:
- 33c340a0c9a273c3c52b4fa3980fb062cf9bc744ba098e138e3fefd7f938108f
- Size of remote file:
- 1.52 GB
- SHA256:
- 5c177b91a84c6e0215b02dd651d14e4da7e6021fb3762e1f06c8b985104908d2
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