convnext-tiny-224-mic / integration.json
tarekziade's picture
tarekziade HF Staff
Publish MIC usage, slim fixture and reviewed Transformers expectations
c0c7b8a verified
Raw History Blame Contribute Delete
2 kB
{
"mic": "0.3",
"name": "ConvNeXT image classification",
"usage": "AutoImageProcessor + AutoModelForImageClassification, batched, synthetic images, inference + one SGD step",
"architecture": "ConvNextForImageClassification",
"checkpoints": {
"facebook/convnext-tiny-224": {
"fixture": "huggingface-mic/convnext-tiny-224-mic"
}
},
"fixtures": {
"huggingface-mic/convnext-tiny-224-mic": {
"built_from": "facebook/convnext-tiny-224",
"covers": [
"facebook/convnext-tiny-224"
],
"build": {
"seed": 17,
"model_class": "ConvNextForImageClassification",
"accept_insensitive": {
"pixel_values:halve": "ConvNeXt normalizes the stem output with LayerNorm, so a uniformly scaled image yields the same features"
}
}
}
},
"integrations": {
"transformers": {
"entry_point": "integrations/transformers/usage.md",
"format": "runnable-markdown",
"requires": [
"transformers>=5",
"torch"
],
"targets": [
"fixtures",
"checkpoints"
],
"variants": {
"default": {},
"eager": {
"attn_implementation": "eager"
},
"bfloat16": {
"dtype": "bfloat16"
}
},
"training": true,
"resources": {
"fixture": {
"memory_gb": 2,
"download_mb": 30
},
"facebook/convnext-tiny-224": {
"memory_gb": 4,
"download_mb": 120
}
}
}
},
"outputs": {
"runtime": {
"compare": "exact"
},
"predicted_labels": {
"compare": "exact"
},
"logits.probe": {
"compare": "allclose",
"atol": 0.0001,
"rtol": 0.0001
},
"training.loss": {
"compare": "allclose",
"atol": 0.0001,
"rtol": 0.0001
},
"training.gradients": {
"compare": "all_true"
},
"training.updated": {
"compare": "true"
}
}
}