Add Q4_0 quantization support for all models in TornadoVM path

[mikepapadim]

Implement complete Q4_0 quantization support following the same pattern as Q8_0:

Core Q4_0 Infrastructure:

• Add Q4_0TornadoTensor for GPU tensor representation with 4-bit quantization
• Implement Q4_0LayerPlanner base class for all Q4_0 planners
• Add LogitsQ4_0Layer shared across all models
• Update ModelLoader to handle Q4_0 tensor creation and loading

Model-Specific Q4_0 Implementations:

• Add LlamaQ4_0LayerPlanner and LlamaQ4_0FFNLayers (also supports Mistral)
• Add Qwen2Q4_0LayerPlanner and Qwen2Q4_0FFNLayers (also supports DeepSeek R1 Distill)
• Add Qwen3Q4_0LayerPlanner and Qwen3Q4_0FFNLayers
• Add Phi3Q4_0LayerPlanner and Phi3Q4_0FFNLayers

Factory and Loader Updates:

• Update QuantizationPlannerFactory to route Q4_0 requests to appropriate planners
• Update all model loaders (Llama, Qwen2, Qwen3, Phi3, Mistral) to accept Q4_0

Q4_0 achieves 4x memory compression vs FP16 and 2x vs Q8_0 while maintaining inference accuracy through per-block quantization with FP16 scale factors. Block size: 32 elements, Type size: 18 bytes (2 bytes FP16 + 16 bytes packed 4-bit values)

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