gftd-260206

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Model Description

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gftd/gftd-260206

GFTD Distilled Model — Claude Opus 4.6 knowledge distilled into Qwen3-8B via QLoRA on Apple MLX.

Training

• Base: Qwen/Qwen3-8B (8.2B params)
• Teacher: Claude Opus 4.6 (via OpenRouter)
• Method: MLX QLoRA (rank=32, layers=8, 200 iters)
• Dataset: 100 samples across 6 categories (all Opus-generated)
• Final Loss: 0.1820
• Eval Score: 100%

Categories

Usage

License

Apache 2.0

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• Language(s) (NLP): en
• License: apache-2.0
• Finetuned from model [optional]: Qwen/Qwen3-8B

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Uses

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Direct Use

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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Training Details

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

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Evaluation

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Testing Data, Factors & Metrics

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Summary

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

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