Instructions to use lindeberg/LaMini-T5-61M_optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lindeberg/LaMini-T5-61M_optimized with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lindeberg/LaMini-T5-61M_optimized") model = AutoModelForSeq2SeqLM.from_pretrained("lindeberg/LaMini-T5-61M_optimized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9460599277556451132366228bffe6f0a38d243bc19889b75b12b7c7ce2fb27d
- Size of remote file:
- 220 MB
- SHA256:
- 0f92d783b4013e8fb0f1e19c29639c49eb7966bcfd446d456f6b4b8854a7626b
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