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chore(model gallery): add smolvlm2-256m-video-instruct (#5417)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2025-05-20 12:03:02 +02:00 • committed by GitHub
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commit 0d590a4044
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gallery/index.yaml
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@ -106,6 +106,25 @@
- filename: mmproj-SmolVLM2-500M-Video-Instruct-f16.gguf
sha256: b5dc8ebe7cbeab66a5369693960a52515d7824f13d4063ceca78431f2a6b59b0
uri: huggingface://ggml-org/SmolVLM2-500M-Video-Instruct-GGUF/mmproj-SmolVLM2-500M-Video-Instruct-f16.gguf
- !!merge <<: *smolvlm
name: "smolvlm2-256m-video-instruct"
icon: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/SmolVLM2_banner.png
urls:
- https://huggingface.co/HuggingFaceTB/SmolVLM2-256M-Video-Instruct
- https://huggingface.co/ggml-org/SmolVLM2-256M-Video-Instruct-GGUF
description: |
SmolVLM2-256M-Video 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 1.38GB of GPU RAM for video inference. This efficiency makes it particularly well-suited for on-device applications that require specific domain fine-tuning and computational resources may be limited.
overrides:
parameters:
model: SmolVLM2-256M-Video-Instruct-Q8_0.gguf
mmproj: mmproj-SmolVLM2-256M-Video-Instruct-Q8_0.gguf
files:
- filename: SmolVLM2-256M-Video-Instruct-Q8_0.gguf
sha256: af7ce9951a2f46c4f6e5def253e5b896ca5e417010e7a9949fdc9e5175c27767
uri: huggingface://ggml-org/SmolVLM2-256M-Video-Instruct-GGUF/SmolVLM2-256M-Video-Instruct-Q8_0.gguf
- filename: mmproj-SmolVLM2-256M-Video-Instruct-Q8_0.gguf
sha256: d34913a588464ff7215f086193e0426a4f045eaba74456ee5e2667d8ed6798b1
uri: huggingface://ggml-org/SmolVLM2-256M-Video-Instruct-GGUF/mmproj-SmolVLM2-256M-Video-Instruct-Q8_0.gguf
- &qwen3
url: "github:mudler/LocalAI/gallery/qwen3.yaml@master"
name: "qwen3-30b-a3b"