Image Classification
Transformers
Safetensors
PyTorch
English
photo_identifier
convnext
multi-class
scene-understanding
object-recognition
wildlife
landmarks
food
custom_code
Eval Results (legacy)
Instructions to use BlakePeavy/photo-identifier-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BlakePeavy/photo-identifier-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BlakePeavy/photo-identifier-v3", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("BlakePeavy/photo-identifier-v3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix: preprocessor_config.json - Colab-ready instructions + suppress char/digit/country/stl labels
ffb153b verified | { | |
| "image_processor_type": "ConvNextImageProcessor", | |
| "use_fast": false, | |
| "do_resize": true, | |
| "size": {"shortest_edge": 256}, | |
| "do_center_crop": true, | |
| "crop_size": {"height": 224, "width": 224}, | |
| "do_rescale": true, | |
| "rescale_factor": 0.00392156862745098, | |
| "do_normalize": true, | |
| "image_mean": [0.485, 0.456, 0.406], | |
| "image_std": [0.229, 0.224, 0.225], | |
| "resample": 3 | |
| } | |