Instructions to use google/gemma-4-12B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-12B-it with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/gemma-4-12B-it") model = AutoModelForImageTextToText.from_pretrained("google/gemma-4-12B-it") - Notebooks
- Google Colab
- Kaggle
Add MMMU Pro evaluation result
#5
by SaylorTwift HF Staff - opened
YAML Metadata Error:Invalid content in Eval Result file .eval_results/mmmu_pro.yaml
Check out the documentation for more information.
Show details
Task ID "mmmu_pro" does not match any task in dataset "MMMU/MMMU_Pro". Available: none
- .eval_results/mmmu_pro.yaml +8 -0
- model.safetensors +1 -1
.eval_results/mmmu_pro.yaml
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- dataset:
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id: MMMU/MMMU_Pro
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task_id: mmmu_pro
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value: 69.1
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date: '2026-05-23'
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source:
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url: https://huggingface.co/google/gemma-4-12B-it
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name: Model Card
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 23919549408
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version https://git-lfs.github.com/spec/v1
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oid sha256:366b79fc7e2ea81106d45e2b3ca10e144925f93dd9d456396692825ddb7bb788
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size 23919549408
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