Instructions to use dacorvo/mnist-mlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dacorvo/mnist-mlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dacorvo/mnist-mlp", 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("dacorvo/mnist-mlp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "MLP" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_mlp.MLPConfig", | |
| "AutoModel": "modeling_mlp.MLP" | |
| }, | |
| "hidden_size": 256, | |
| "input_size": 784, | |
| "model_type": "mlp", | |
| "output_size": 10, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.34.0" | |
| } | |