Instructions to use xformAI/opt-6.7b-ub-16-gqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xformAI/opt-6.7b-ub-16-gqa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xformAI/opt-6.7b-ub-16-gqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: mit
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license: mit
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library_name: transformers
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This is a GQA version of the original model facebook/opt-125m. In this version, the original MHA architecture is preserved but instead of having a single K/V head, different K/V heads corresponding to the same group have the same mean-pooled K or V values. It has 16 groups of KV heads per layer instead of original 32 KV heads in the MHA implementation.
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