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cv-classification
Best practices for image classification tasks. Use when working on CIFAR, ImageNet, or other classification benchmarks.
DeepseekModel
Curated skill
Quality Excellent · 90
v1.0.0
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https://deepseekmodel.com/api/download.php?id=aiming-lab-autoresearchclaw-researchclaw-skills-builtin-domain-cv-classification-skill-md&format=skill
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Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name cv-classification description Best practices for image classification tasks. Use when working on CIFAR, ImageNet, or other classification benchmarks. metadata {"category":"domain","trigger-keywords":"classification,image,cifar,imagenet,resnet,vision,cnn,vit","applicable-stages":"9,10","priority":"3","version":"1.0","author":"researchclaw","references":"He et al., Deep Residual Learning, CVPR 2016; Dosovitskiy et al., An Image is Worth 16x16 Words, ICLR 2021"} Image Classification Best Practice Architecture selection: Small scale (CIFAR-10/100): ResNet-18/34, WideResNet, Simple ViT Medium scale: ResNet-50, EfficientNet-B0/B1, DeiT-Small Large scale: ViT-B/16, ConvNeXt, Swin Transformer Training recipe: Optimizer: AdamW (lr=1e-3 to 3e-4) or SGD (lr=0.1 with cosine decay) Weight decay: 0.01-0.1 for AdamW, 5e-4 for SGD Data augmentation: RandomCrop, RandomHorizontalFlip, Cutout/CutMix Warmup: 5-10 epochs linear warmup for transformers Batch size: 128-256 for CNNs, 512-1024 for ViTs (if memory allows) Standard benchmarks: CIFAR-10: ~96% (ResNet-18), ~97% (WideResNet) CIFAR-100: ~80% (ResNet-18), ~84% (WideResNet) ImageNet: ~76% (ResNet-50), ~81% (ViT-B/16)
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The downloaded .skill package contains the following fields.
| Field | Description |
|---|---|
| format | Format tag (skill/v1) |
| skill_id | Unique skill ID |
| name | Skill name |
| version | Version |
| description | Description |
| category | Categories (array) |
| trigger_words | Trigger words |
| tags | Tags |
| source | Source |
| source_url | Source URL (this page) |
| exported_at | Exported at (set per download) |
| system_prompt | System prompt body |
| model_config | Model config: provider / model / temperature / max_tokens / top_p |
| examples | Examples |
| install_guide | Import guide for Coze / Dify / Claude / custom frameworks |
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