Instructions to use google/flan-ul2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/flan-ul2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/flan-ul2") model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-ul2") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Running the model
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For more efficient memory usage, we advise you to load the model in `8bit` using `load_in_8bit` flag as follows:
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```python
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# pip install accelerate transformers bitsandbytes
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## Running the model
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For more efficient memory usage, we advise you to load the model in `8bit` using `load_in_8bit` flag as follows (works only under GPU):
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```python
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# pip install accelerate transformers bitsandbytes
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