Instructions to use RamsesDIIP/mt5-large-ie-budquo-5k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RamsesDIIP/mt5-large-ie-budquo-5k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RamsesDIIP/mt5-large-ie-budquo-5k") model = AutoModelForSeq2SeqLM.from_pretrained("RamsesDIIP/mt5-large-ie-budquo-5k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84996aaf59594ff2fd56e527a5d5efa76aa4c6ad0ab146f323c5081fd4f4040a
- Size of remote file:
- 5.3 kB
- SHA256:
- 74d4bf80c5a8a88706fcb8ad9b1a1b91698d579de185e32f27f0cb571d12d33e
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