Summarization
Transformers
Safetensors
English
bart
text2text-generation
scihigh-2026
research-highlight-generation
scientific-summarization
seq2seq
Instructions to use uthayamurthy/origin-task1-bart-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uthayamurthy/origin-task1-bart-large with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="uthayamurthy/origin-task1-bart-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uthayamurthy/origin-task1-bart-large") model = AutoModelForSeq2SeqLM.from_pretrained("uthayamurthy/origin-task1-bart-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from uthayamurthy/origin-task1-bart-large: direct link, hf CLI and curl.
- Browser
- Download file 6.03 kB
-
https://huggingface.co/uthayamurthy/origin-task1-bart-large/resolve/main/training_args.bin
- Command line
-
hf download hf://uthayamurthy/origin-task1-bart-large/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/uthayamurthy/origin-task1-bart-large/resolve/main/training_args.bin
6.03 kB
- Xet hash:
- 2db42bb7881f2b208ab93c803c2b3158e8db2db96eb64eeff002eef2017544fc
- Size of remote file:
- 6.03 kB
- SHA256:
- ca677474bfdf5fb65443a5f77fa54558d8bf4f7ed28e55b28054f8fe3a34a53d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.