Any-to-Any
Transformers
Safetensors
MLX
gemma4_unified
image-text-to-text
nightmedia
gemma4
gemma
google
startrek
coding
finetune
8-bit precision
Instructions to use nightmedia/gemma-4-12B-TNG-V1-q8-hi-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nightmedia/gemma-4-12B-TNG-V1-q8-hi-mlx with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("nightmedia/gemma-4-12B-TNG-V1-q8-hi-mlx") model = AutoModelForMultimodalLM.from_pretrained("nightmedia/gemma-4-12B-TNG-V1-q8-hi-mlx", device_map="auto") - MLX
How to use nightmedia/gemma-4-12B-TNG-V1-q8-hi-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download nightmedia/gemma-4-12B-TNG-V1-q8-hi-mlx --local-dir gemma-4-12B-TNG-V1-q8-hi-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Update README.md
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README.md
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license_link: https://ai.google.dev/gemma/docs/gemma_4_license
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pipeline_tag: any-to-any
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base_model: google/gemma-4-12B-it
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tags:
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- nightmedia
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- gemma4
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license_link: https://ai.google.dev/gemma/docs/gemma_4_license
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pipeline_tag: any-to-any
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base_model: google/gemma-4-12B-it
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library_name: transformers
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tags:
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- nightmedia
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- gemma4
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