Instructions to use sheoran95/augmented_data_without_edge_document_level_BART_run3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sheoran95/augmented_data_without_edge_document_level_BART_run3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sheoran95/augmented_data_without_edge_document_level_BART_run3") model = AutoModelForSeq2SeqLM.from_pretrained("sheoran95/augmented_data_without_edge_document_level_BART_run3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sheoran95/augmented_data_without_edge_document_level_BART_run3: direct link, hf CLI and curl.
- Browser
- Download file 3.84 kB
-
https://huggingface.co/sheoran95/augmented_data_without_edge_document_level_BART_run3/resolve/main/training_args.bin
- Command line
-
hf download hf://sheoran95/augmented_data_without_edge_document_level_BART_run3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sheoran95/augmented_data_without_edge_document_level_BART_run3/resolve/main/training_args.bin
3.84 kB
- Xet hash:
- facf19283766cf7b5c8cec186614c877ea98f82f3aaf3f8261ccf914c4c8de7a
- Size of remote file:
- 3.84 kB
- SHA256:
- 646d1d4b7000da18e7408ffad91c1401eb94e7232462cffb777e57f823e9696d
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