Instructions to use google/flan-t5-xxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/flan-t5-xxl with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-xxl") model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-xxl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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The model was trained on a mixture of tasks, that includes the tasks described in the table below (from the original paper, figure 2):
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. See the table below for some quantitative evaluation:
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## Results
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The model was trained on a mixture of tasks, that includes the tasks described in the table below (from the original paper, figure 2):
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## Training Procedure
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## Testing Data, Factors & Metrics
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The authors evaluated the model on various tasks covering several languages (1836 in total). See the table below for some quantitative evaluation:
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For full details, please check the [research paper](https://arxiv.org/pdf/2210.11416.pdf).
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## Results
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