Instructions to use zbigi/bart-base-summarization-cnn-49 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zbigi/bart-base-summarization-cnn-49 with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-base") model = PeftModel.from_pretrained(base_model, "zbigi/bart-base-summarization-cnn-49") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zbigi/bart-base-summarization-cnn-49: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/zbigi/bart-base-summarization-cnn-49/resolve/main/training_args.bin
- Command line
-
hf download hf://zbigi/bart-base-summarization-cnn-49/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/zbigi/bart-base-summarization-cnn-49/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- dde239f5944a3242ec9b3e507cb3f5fe6a21ede35f3e56472e398d8e79c3ca18
- Size of remote file:
- 5.43 kB
- SHA256:
- 2f269b89b6018e9f2c70fef4d8cc0389e03d5b9190768958d5924af8726d1e3f
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