Add global scale support to quantized layers

[aleroot]

Store optional globalScale on QuantizedLinear and QuantizedEmbedding so nvfp4 weights can preserve the scale needed by lower-level MLX quantize/dequantize operations.

Forward the scale when creating or dequantizing weights, add a direct pre-quantized QuantizedEmbedding initializer to match QuantizedLinear, and guard global-scale execution paths on Metal because MLX does not support globalScale dequantization there.

Add focused tests for the new layer state and parameter exposure without broadening the generic quantization API surface.

Proposed changes

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[davidkoski]

One thing we need to be careful of here is that there is currently no python support for this. That means:

• maybe we want to set the key as global_scale or global_scales to match the likely python naming
• if this is non-nil after quantizing the model, it will be required when loading weights
  • will this cause a problem or is nvfp4 just not used?

[aleroot]

Good point. I changed the serialised parameter key to global_scale

[davidkoski]

I like it, but see my questions -- I think these need some thought before merging.