Transformers
PyTorch
Safetensors
mbart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use mukayese/mbart-large-turkish-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mukayese/mbart-large-turkish-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mukayese/mbart-large-turkish-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mukayese/mbart-large-turkish-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97b96a259bde66dd94b35e38178ebfc5586a5fb33450785acf0967a224c0ed83
- Size of remote file:
- 2.44 GB
- SHA256:
- ae44ca016a350017780d65061173081b121bae883bec55fd702a86edb70d18d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.