Instructions to use Patcas/plbart-docs-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Patcas/plbart-docs-v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Patcas/plbart-docs-v1") model = AutoModelForSeq2SeqLM.from_pretrained("Patcas/plbart-docs-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Patcas/plbart-docs-v1: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Patcas/plbart-docs-v1/resolve/main/training_args.bin
- Command line
-
hf download hf://Patcas/plbart-docs-v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Patcas/plbart-docs-v1/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 5e08ab1590a2d42533749c4dfcdd972fc2420307ca4e90ba4a2c44faf5d51e39
- Size of remote file:
- 4.73 kB
- SHA256:
- 9cbbbf4ba2282c4209fd8d111fe05c99d00eeccc8c846b71b457e177468926fc
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