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SmolVLM2-256M-Video-Instruct-ternary – AI Model by AsadIsmail | AlphaNeural AI
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AsadIsmail
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SmolVLM2-256M-Video-Instruct-ternary
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transformers
ternary-quant
quantization
ternary
vlm
multimodal
video
edge
smolvlm
image-text-to-text
en
HuggingFaceTB/SmolVLM2-256M-Video-Instruct
finetune
apache-2.0
endpoints_compatible
us
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SmolVLM2-256M-Video-Instruct — Ternary Quantized (tritplane3)
Ternary-quantized version
of
HuggingFaceTB/SmolVLM2-256M-Video-Instruct
— the smallest video-understanding VLM, now even smaller. Ideal for edge deployment.
Specifications
Property
Value
Base Model
HuggingFaceTB/SmolVLM2-256M-Video-Instruct
Parameters
256M
Quantization
tritplane3 (211 linear layers)
Full-model effective bits
12.91
Compression ratio
1.24×
Avg reconstruction error
0.1488
Collection
Part of
ternary-models
.