Instructions to use henryscheible/qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/qqp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/qqp") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/qqp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/qqp: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/henryscheible/qqp/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/qqp/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/qqp/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 8d42095d495fcce70186fb6df68ccd9257f08a4d1c6cb267b0369dfb3bfcc62e
- Size of remote file:
- 438 MB
- SHA256:
- 2e4e5f22e98f07ec8ed4e4f62980bdd4cb41ad1d845b87fa7a21dc2d81c42271
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