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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ base_model: deepreinforce-ai/Ornith-1.0-35B
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+ library_name: mlx
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+ tags:
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+ - mlx
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+ - vision
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+ pipeline_tag: image-text-to-text
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+ ---
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+
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+ # ToPo-ToPo/Ornith-1.0-35B-mlx-bf16
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+
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+ MLX **bf16** conversion of [`deepreinforce-ai/Ornith-1.0-35B`](https://huggingface.co/deepreinforce-ai/Ornith-1.0-35B) for Apple Silicon (mlx-vlm).
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+
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+ ## Provenance (self-converted from official weights)
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+ - Source: [`deepreinforce-ai/Ornith-1.0-35B`](https://huggingface.co/deepreinforce-ai/Ornith-1.0-35B) (license: mit)
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+ - Tool: `mlx-vlm 0.6.3` — `mlx_vlm.convert --hf-path deepreinforce-ai/Ornith-1.0-35B --mlx-path . --dtype bfloat16`
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+ - Effective: **16.0 bits/weight**
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+ - Note (MoE): the source stores experts per-expert (`experts.{i}.gate_proj/up_proj/down_proj`), while mlx-vlm expects a fused/stacked `experts.gate_up_proj`. A `sanitize` monkeypatch fused them before conversion (gate then up, stacked over experts).
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+ - Validation: reproduced geometrically exact CAD output in an agentic CAD+FEM pipeline
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+ (volumes match the reference mlx-community conversion).
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+
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+ ## Usage
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+ ```python
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+ from mlx_vlm import load, generate
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+ model, processor = load("ToPo-ToPo/Ornith-1.0-35B-mlx-bf16")
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+ ```
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+ {%- endif %}
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+ {{- raise_exception('System message cannot contain videos.') }}
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+ {%- if add_vision_id %}
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+ {{- 'Video ' ~ video_count.value ~ ': ' }}
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+ {%- endif %}
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+ {%- elif 'text' in item %}
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+ {{- item.text }}
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+ {{- raise_exception('Unexpected item type in content.') }}
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+ {%- endif %}
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+ {{- '' }}
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