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:
# pip install -U transformers accelerate # 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
Download decoder_model_optimized.onnx from lindeberg/LaMini-T5-61M_optimized: direct link, hf CLI and curl.
- Browser
- Download file 232 MB
-
https://huggingface.co/lindeberg/LaMini-T5-61M_optimized/resolve/main/decoder_model_optimized.onnx
- Command line
-
hf download hf://lindeberg/LaMini-T5-61M_optimized/decoder_model_optimized.onnx
-
curl -L -o decoder_model_optimized.onnx https://huggingface.co/lindeberg/LaMini-T5-61M_optimized/resolve/main/decoder_model_optimized.onnx
232 MB
- Xet hash:
- 5036872ec90f94bebda96903db269aba3f793f23b4f045dd9c4913e9b63d1820
- Size of remote file:
- 232 MB
- SHA256:
- 11122d970641287fd4c746e71ca0fe29c28e48c0e86f955be7dfb786e968408b
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