Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use devagonal/mt5-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devagonal/mt5-semantic with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("devagonal/mt5-semantic") model = AutoModelForSeq2SeqLM.from_pretrained("devagonal/mt5-semantic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a8b4b00063c9eb7f8dfc4b9ae3a4a36c8deb0cf5d200d7fa04cb798cf67d675
- Size of remote file:
- 2.33 GB
- SHA256:
- 5edf715553730963dc9510891571ea7725d862a77efef1cc01c22baf753aa7b8
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