Sync model repo (text/metadata)

README.md

@@ -53,10 +53,38 @@ image dimensions up to 4096×4096, crops the largest top-left square, resizes it
 
 ## 🚀 Get Started with the Model
 
-### 🔓 Compute Flow — Early Access
+### Run with Compute Flow
 
-The inference engine for this model package is available through the Compute Flow Early Access
-Program. Contact ai-early-access@arm.com to request access.
+Follow these steps to run ZipDepth Base FP16 — ExecuTorch on macOS® with Apple Silicon or on
+Linux® with an Arm®-based CPU, such as a Raspberry Pi® 5.
+
+#### Step 1: Clone Compute Flow and set up the virtual environment
+
+```bash
+git clone https://github.com/ARM-software/ComputeFlow.git && cd ComputeFlow
+
+uv sync && source .venv/bin/activate
+```
+
+#### Step 2: Install the brick and model
+
+```bash
+compute-flow update
+compute-flow model install monocular_depth_estimation:zip-depth zipdepth-base-executorch-fp16
+compute-flow build native
+```
+
+#### Step 3: Run the Python CLI example
+
+```bash
+python -m cli_examples.monocular_depth_estimation_cli \
+  -m @manifest/zip-depth/zipdepth-base-executorch-fp16/zipdepth_manifest.json \
+  -i @sample/im0.jpg \
+  -t 1
+```
+
+The example estimates relative depth for the bundled `samples/im0.jpg` image. Replace `-i` with a
+path to your own image.
 
 ## 📊 Quality evaluation
 

SHA256SUMS

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