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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Ettore Di Giacinto 2025-05-20 11:36:22 +02:00 committed by GitHub
parent 8caaf49f5d
commit 6bc2ae5467
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@ -66,6 +66,25 @@
- filename: mmproj-SmolVLM-Instruct-Q8_0.gguf
sha256: 86b84aa7babf1ab51a6366d973b9d380354e92c105afaa4f172cc76d044da739
uri: https://huggingface.co/ggml-org/SmolVLM-Instruct-GGUF/resolve/main/mmproj-SmolVLM-Instruct-Q8_0.gguf
- !!merge <<: *smolvlm
name: "smolvlm2-2.2b-instruct"
icon: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/SmolVLM2_banner.png
urls:
- https://huggingface.co/HuggingFaceTB/SmolVLM2-2.2B-Instruct
- https://huggingface.co/ggml-org/SmolVLM2-2.2B-Instruct-GGUF
description: |
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.
overrides:
parameters:
model: SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
mmproj: mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf
files:
- filename: SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
sha256: 0cf76814555b8665149075b74ab6b5c1d428ea1d3d01c1918c12012e8d7c9f58
uri: huggingface://ggml-org/SmolVLM2-2.2B-Instruct-GGUF/SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
- filename: mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf
sha256: ae07ea1facd07dd3230c4483b63e8cda96c6944ad2481f33d531f79e892dd024
uri: huggingface://ggml-org/SmolVLM2-2.2B-Instruct-GGUF/mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf
- &qwen3
url: "github:mudler/LocalAI/gallery/qwen3.yaml@master"
name: "qwen3-30b-a3b"