Instructions to use ybelkada/tiny-random-T5ForConditionalGeneration-calibrated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ybelkada/tiny-random-T5ForConditionalGeneration-calibrated with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ybelkada/tiny-random-T5ForConditionalGeneration-calibrated") model = AutoModelForSeq2SeqLM.from_pretrained("ybelkada/tiny-random-T5ForConditionalGeneration-calibrated", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (0876f9e6b2a27e6214543ffad8b630fcbb9094a5) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>9acf6d6
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Create README.md
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Upload T5ForConditionalGeneration
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initial commit
Younes Belkadad37340a