Instructions to use nbroad/mt5-small-qgen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/mt5-small-qgen with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nbroad/mt5-small-qgen") model = AutoModelForSeq2SeqLM.from_pretrained("nbroad/mt5-small-qgen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (1baeaaf4f503b7b31b3f112dbe03016eeebc5201) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>5235927
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Add multilingual to the language tag (#2)
- Add multilingual to the language tag (25d6af1b954e3e0508642cf7119e5a88a3c8b7f9) - Fix non-ascii characters (1ad6e5955f1189b79de89583bb66178caaca6535) Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>20ec11f
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remove flax example
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add pt and tf weights
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change return_tensors to "np" for flax example
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intended use and limitations
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add widget examples
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Update README.md
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Update README.md
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Update README.md
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Create README.md
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Saving weights and logs of epoch 2
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Saving weights and logs of epoch 1
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Saving weights and logs of epoch 0
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Upload run_summarization_flax.py
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Upload start_qgen.sh
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initial commit
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