feat: full multimodal MLX weights (vision + audio towers)

Re-quantized with mlx-vlm from google/gemma-4-e2b-it.
2,649 tensors: language_model + vision_tower + audio_tower + embeddings.
Verified: mlx-vlm correctly describes images at 132 tok/s.

Co-Authored-By: Cladius Maximus <cladius@lethean.io>

README.md

@@ -207,8 +207,8 @@ formatted_prompt = apply_chat_template(
     processor, config, prompt, num_images=1
 )
 
-output = generate(model, processor, formatted_prompt, image)
-print(output)
+output = generate(model, processor, formatted_prompt, image, max_tokens=200)
+print(output.text)
 ```
 </details>
 

config.json

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@@ -198,4 +1038,4 @@
         "use_clipped_linears": true
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     "vision_soft_tokens_per_image": 280
-}
+}

model.safetensors

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