Instructions to use devagonal/mt5-semantic-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devagonal/mt5-semantic-2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("devagonal/mt5-semantic-2") model = AutoModelForSeq2SeqLM.from_pretrained("devagonal/mt5-semantic-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- caaa5c2a75119ca4fb340fb55bdc16a2c9ee335f80db0534800f80b298acf80a
- Size of remote file:
- 2.33 GB
- SHA256:
- 4e66fd92920acd95c7840e7df6ea44df63787e86d87d88430f8d5a1a4c5caad4
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