Instructions to use dnrso/koBART_Sum_Review_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dnrso/koBART_Sum_Review_finetuning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dnrso/koBART_Sum_Review_finetuning") model = AutoModelForSeq2SeqLM.from_pretrained("dnrso/koBART_Sum_Review_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from dnrso/koBART_Sum_Review_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 310 Bytes
-
https://huggingface.co/dnrso/koBART_Sum_Review_finetuning/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://dnrso/koBART_Sum_Review_finetuning/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/dnrso/koBART_Sum_Review_finetuning/resolve/main/tokenizer_config.json
310 Bytes
| { | |
| "name_or_path": "digit82/kobart-summarization", | |
| "special_tokens_map_file": "/Users/digit82/.cache/huggingface/transformers/3e6abf40f4fadbea9e7b539c182868d979838d8f7e6cdcdf2ed52ddcf01420c0.15447ae63ad4a2eba8bc7a5146360711dc32b315b4f1488b4806debf35315e9a", | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |