Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix typo in Python code block on home page #21196

Merged
merged 2 commits into from
Jun 27, 2024
Merged

Fix typo in Python code block on home page #21196

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a7a8871
Fix typo in Python code block on home page
sophies927 Jun 27, 2024
5941902
Fix broken mobilenet_v2 download link
sophies927 Jun 27, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/tutorials/mobile/deploy-android.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ The pre-trained [TorchVision MOBILENET V2](https://pytorch.org/hub/pytorch_visio
- Quantize the FP32 ONNX model to an uint8 ONNX model
- Convert both FP32 and uint8 ONNX models to ORT models

Note: this step is optional, you can download the FP32 and uint8 ORT models [here](https://onnxruntimeexamplesdata.z13.web.core.windows.net/mobilenet_v2_ort_models.zip).
Note: this step is optional, you can download the FP32 and uint8 ORT models [here](https://github.com/onnx/models/tree/main/validated/vision/classification/mobilenet/model).

2. Download the model class labels

Expand Down
2 changes: 1 addition & 1 deletion src/routes/components/code-blocks.svelte
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@
import github from "svelte-highlight/styles/github";

let pythonCode =
'import onnxruntime as ort\n# Load the model and create InferenceSession\nmodel_path = "path/to/your/onnx/model"\nsession = ort.InferenceSession(model_path)\n# "Load and preprocess the input image inputTensor"\n...\n# Run inference\noutputs = session.run(None {"input": inputTensor})\nprint(outputs)';
'import onnxruntime as ort\n# Load the model and create InferenceSession\nmodel_path = "path/to/your/onnx/model"\nsession = ort.InferenceSession(model_path)\n# "Load and preprocess the input image inputTensor"\n...\n# Run inference\noutputs = session.run(None, {"input": inputTensor})\nprint(outputs)';
let csharpCode =
'using Microsoft.ML.OnnxRuntime;\n// Load the model and create InferenceSession\nstring model_path = "path/to/your/onnx/model";\nvar session = new InferenceSession(model_path);\n// Load and preprocess the input image to inputTensor\n...\n// Run inference\nvar outputs = session.Run(inputTensor).ToList();\nConsole.WriteLine(outputs[0].AsTensor()[0]);';
let javascriptCode =
Expand Down
Loading