atad-tokyo/GST_EGOSCHEMA
Model Card for Model ID https://showlab.github.io/videollm-online/ Model Details LLM: meta-llama/Meta-Llama-3-8B-Instruct Vision Strategy: Frame Encoder: google/siglip-large-patch16-384 Frame Tokens: CLS Token + Avg Pooled 3x3 Tokens Frame FPS: 2 for training, 2~10 for inference Frame Resolution: max resolution 384, with zero-padding to keep aspect ratio Video Length: 10 minutes Training Data: Ego4D Narration Stream 113K + Ego4D GoalStep Stream 21K… See the full description on the dataset page: https://huggingface.co/datasets/atad-tokyo/GST_EGOSCHEMA.
| Author / organization | atad-tokyo |
|---|---|
| License (as declared) | mit |
| Downloads | 183 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 8 February 2026 |
| Last updated at source | 8 February 2026 |
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183 now (-477 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: Model Card for Model ID https://showlab.github.io/videollm-online/ Model Details LLM: meta-llama/Meta-Llama-3-8B-Instruct Vision Strategy: Frame Encoder: google/siglip-large-patch16-384 Frame Tokens: CLS Token + Avg Pooled 3x3 Tokens Frame → Model Card for Model ID https://showlab.github.io/videollm-online/ Model Details LLM: meta-llama/Meta-Llama-3-8B-Instruct Vision Strategy: Frame Encoder: google/siglip-large-patch16-384 Frame Tokens: CLS Token + Avg Pooled 3x3 Tokens Frame
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More from atad-tokyo
- atad-tokyo/cxkDataset
- atad-tokyo/GST_EGOSERVEDataset
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