Instructions to use ULRs/mt5-large-summarization-ur with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ULRs/mt5-large-summarization-ur with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ULRs/mt5-large-summarization-ur") model = AutoModelForSeq2SeqLM.from_pretrained("ULRs/mt5-large-summarization-ur", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bc259c646ea1b6c16984693fde604b87ce7ca2ffa0f4b8e82df93827fb144cc
- Size of remote file:
- 5.24 kB
- SHA256:
- 2d2cfc5db86539f0c7c189c4044e7c98481ff10fc16efe1df165621860b17a49
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