Transformers
Safetensors
Indonesian
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use apwic/summarization-base-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apwic/summarization-base-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("apwic/summarization-base-4") model = AutoModelForSeq2SeqLM.from_pretrained("apwic/summarization-base-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from apwic/summarization-base-4: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/apwic/summarization-base-4/resolve/main/training_args.bin
- Command line
-
hf download hf://apwic/summarization-base-4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/apwic/summarization-base-4/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 2b18f30ac02597d9bd4947fb73a1b541804723defc7dcffa1db52a429b196197
- Size of remote file:
- 5.18 kB
- SHA256:
- e5a86f852edc7bb5ee8edbc4678ed601fc009f570d7ce067cf08b1c900b504bd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.