SkyContact/VideoMAE-base-GGUF
video-classification model by SkyContact
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Model card & documentation
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GGUF conversion of MCG-NJU/videomae-base (pretraining release) and MCG-NJU/videomae-base-finetuned-kinetics (Kinetics-400 classifier), packaged for the SkyVision.cpp inference engine. VideoMAE-base is a pure video tower (94M parameters, no text decoder, no tokenizer, no KV cache): 16 uniform frames → bicubic resize + center crop 224 → one full space-time attention pass over 1568 tokens → either a Kinetics-400 label distribution or the pooled 768-d embedding. CPU: 0.85 s per clip (16 frames / 1568 tokens / 12 layers) on an i7-14700K with F16 weights, 0.6 s with the Q80 file. --ask is meaningless for this architecture and is ignored. the official implementation (t', h', w') with element order (c, dt, dh, dw); qbias | 0 | vbias; mean over tokens + fcnorm (no…
Read the full model card ↗ · Preview checked 2026-10-30T12:05:29.632Z
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Model overview
SkyContact/VideoMAE-base-GGUF is a video-classification model repository published by SkyContact on Hugging Face. The source reports the gguf library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- video-classification
- Library
- gguf
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- cc-by-nc-4.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-17T06:23:59.000Z
- Last modified
- 2026-10-17T06:24:57.000Z
Compatibility and lineage
Reported languages: en
Reported base models: MCG-NJU/videomae-base, MCG-NJU/videomae-base-finetuned-kinetics
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-17T06:42:57.152Z. Daily imports are snapshots, not real-time monitoring.
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