Instructions to use Yodazon/3DPrintFailureType with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yodazon/3DPrintFailureType with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="Yodazon/3DPrintFailureType")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Yodazon/3DPrintFailureType", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "pyTorchModel", | |
| "num_classes": 4, | |
| "layers": [ | |
| { | |
| "type": "Conv2d", | |
| "in_channels": 3, | |
| "out_channels": 96, | |
| "kernel_size": 11, | |
| "stride": 4, | |
| "padding": 0 | |
| }, | |
| { | |
| "type": "BatchNorm2d", | |
| "num_features": 96 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "MaxPool2d", | |
| "kernel_size": 3, | |
| "stride": 2 | |
| }, | |
| { | |
| "type": "Conv2d", | |
| "in_channels": 96, | |
| "out_channels": 256, | |
| "kernel_size": 5, | |
| "stride": 1, | |
| "padding": 2 | |
| }, | |
| { | |
| "type": "BatchNorm2d", | |
| "num_features": 256 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "MaxPool2d", | |
| "kernel_size": 3, | |
| "stride": 2 | |
| }, | |
| { | |
| "type": "Conv2d", | |
| "in_channels": 256, | |
| "out_channels": 384, | |
| "kernel_size": 3, | |
| "stride": 1, | |
| "padding": 1 | |
| }, | |
| { | |
| "type": "BatchNorm2d", | |
| "num_features": 384 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "Conv2d", | |
| "in_channels": 384, | |
| "out_channels": 384, | |
| "kernel_size": 3, | |
| "stride": 1, | |
| "padding": 1 | |
| }, | |
| { | |
| "type": "BatchNorm2d", | |
| "num_features": 384 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "Conv2d", | |
| "in_channels": 384, | |
| "out_channels": 256, | |
| "kernel_size": 3, | |
| "stride": 1, | |
| "padding": 1 | |
| }, | |
| { | |
| "type": "BatchNorm2d", | |
| "num_features": 256 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "MaxPool2d", | |
| "kernel_size": 3, | |
| "stride": 2 | |
| }, | |
| { | |
| "type": "Dropout", | |
| "p": 0.5 | |
| }, | |
| { | |
| "type": "Linear", | |
| "in_features": 9216, | |
| "out_features": 4096 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "Dropout", | |
| "p": 0.5 | |
| }, | |
| { | |
| "type": "Linear", | |
| "in_features": 4096, | |
| "out_features": 4096 | |
| }, | |
| { | |
| "type": "ReLU" | |
| }, | |
| { | |
| "type": "Linear", | |
| "in_features": 4096, | |
| "out_features": 4 | |
| } | |
| ] | |
| } | |