examples
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@ -32,10 +32,22 @@ graph TB
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subgraph Hardware["Backend Execution Layer"]
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subgraph Hardware["Backend Execution Layer"]
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direction TB
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direction TB
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backend_impl[" The backend package provides:<br>- Unified computation interface<br>- Automatic hardware selection<br>- Optimized kernels<br>- Efficient memory management "]
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backend_impl[" The backend package provides:<br>- Unified computation interface<br>- Automatic hardware selection<br>- Optimized kernels<br>- Efficient memory management "]
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subgraph Backends["Backend Implementations"]
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direction LR
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cpu["backend/cpu<br>- Pure Go implementation<br>- Fallback for all platforms"]
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metal["backend/metal<br>- Apple Silicon (M1/M2/M3)<br>- MLX integration<br>- Leverages Apple Neural Engine"]
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onnx["backend/onnx<br>- Cross-platform compatibility<br>- ONNX Runtime integration<br>- Pre-compiled graph execution"]
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ggml["backend/ggml<br>- CPU/GPU quantized compute<br>- Low-precision operations<br>- Memory-efficient inferencing"]
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end
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end
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end
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Models --> |" Makes high-level calls<br>(e.g., self-attention) "| ML_Ops
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Models --> |" Makes high-level calls<br>(e.g., self-attention) "| ML_Ops
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ML_Ops --> |" Translates to tensor operations<br>(e.g., matmul, softmax) "| Hardware
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ML_Ops --> |" Translates to tensor operations<br>(e.g., matmul, softmax) "| Hardware
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backend_impl --> Backends
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```
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```
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When implementing a new model, you'll primarily work in the model layer, interfacing with the neural network operations layer.
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When implementing a new model, you'll primarily work in the model layer, interfacing with the neural network operations layer.
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@ -323,4 +335,4 @@ To open a draft PR:
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```bash
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```bash
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ollama create <your-namespace>/<your-model> -f /path/to/Modelfile
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ollama create <your-namespace>/<your-model> -f /path/to/Modelfile
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ollama push <your-namespace>/<your-model>
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ollama push <your-namespace>/<your-model>
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```
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```
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