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chore(model gallery): add smolvlm2-2.2b-instruct (#5415)
chore(model gallery): add smolvlm-instruct Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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@ -66,6 +66,25 @@
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- filename: mmproj-SmolVLM-Instruct-Q8_0.gguf
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sha256: 86b84aa7babf1ab51a6366d973b9d380354e92c105afaa4f172cc76d044da739
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uri: https://huggingface.co/ggml-org/SmolVLM-Instruct-GGUF/resolve/main/mmproj-SmolVLM-Instruct-Q8_0.gguf
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- !!merge <<: *smolvlm
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name: "smolvlm2-2.2b-instruct"
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icon: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/SmolVLM2_banner.png
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urls:
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- https://huggingface.co/HuggingFaceTB/SmolVLM2-2.2B-Instruct
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- https://huggingface.co/ggml-org/SmolVLM2-2.2B-Instruct-GGUF
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description: |
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SmolVLM2-2.2B is a lightweight multimodal model designed to analyze video content. The model processes videos, images, and text inputs to generate text outputs - whether answering questions about media files, comparing visual content, or transcribing text from images. Despite its compact size, requiring only 5.2GB of GPU RAM for video inference, it delivers robust performance on complex multimodal tasks. This efficiency makes it particularly well-suited for on-device applications where computational resources may be limited.
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overrides:
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parameters:
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model: SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
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mmproj: mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf
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files:
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- filename: SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
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sha256: 0cf76814555b8665149075b74ab6b5c1d428ea1d3d01c1918c12012e8d7c9f58
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uri: huggingface://ggml-org/SmolVLM2-2.2B-Instruct-GGUF/SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
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- filename: mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf
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sha256: ae07ea1facd07dd3230c4483b63e8cda96c6944ad2481f33d531f79e892dd024
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uri: huggingface://ggml-org/SmolVLM2-2.2B-Instruct-GGUF/mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf
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- &qwen3
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url: "github:mudler/LocalAI/gallery/qwen3.yaml@master"
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name: "qwen3-30b-a3b"
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