Instructions to use Gaxys/MPnet-PD_Books with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gaxys/MPnet-PD_Books with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gaxys/MPnet-PD_Books")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gaxys/MPnet-PD_Books") model = AutoModelForSequenceClassification.from_pretrained("Gaxys/MPnet-PD_Books", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Gaxys/MPnet-PD_Books: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Gaxys/MPnet-PD_Books/resolve/main/training_args.bin
- Command line
-
hf download hf://Gaxys/MPnet-PD_Books/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Gaxys/MPnet-PD_Books/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- d23c47b86b60fc99feb376134990a876ef8de74b6c37c9e047d7a6b906452b47
- Size of remote file:
- 4.54 kB
- SHA256:
- d98c1884cb4fedfb2db81a9c15c1572a8ac800950edd618c3f9e02ed1d20c28c
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