Image Classification
PyTorch
Safetensors
Transformers
English
resnet10
feature-extraction
jax-conversion
resnet
hil-serl
Lerobot
vision
custom_code
Instructions to use helper2424/resnet10_test_port with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helper2424/resnet10_test_port with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="helper2424/resnet10_test_port", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("helper2424/resnet10_test_port", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 407 Bytes
50d4f45 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"crop_pct": 1,
"data_format": "channels_first",
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"do_scale": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "ConvNextImageProcessorFast",
"image_std": [
0.229,
0.224,
0.225
],
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"shortest_edge": 128
}
}
|