Instructions to use microsoft/prophetnet-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/prophetnet-large-uncased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("microsoft/prophetnet-large-uncased") model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/prophetnet-large-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/prophetnet-large-uncased: direct link, hf CLI and curl.
- Browser
- Download file 1.57 GB
-
https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/prophetnet-large-uncased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/pytorch_model.bin
1.57 GB
- Xet hash:
- 0feca0ab1dd6cd1386fe757b4c1873f234717e7f439608aca358b2422618b7f6
- Size of remote file:
- 1.57 GB
- SHA256:
- cedef47113e2d8b06409b81df84b67143f2cc9e4b2b334aee6ae1e74e1f1728a
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