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audreyt/Ornith-1.5-9B-DFlash-GGUF
Ornith-1.5-9B-DFlash-GGUF is a machine learning model from audreyt. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as apache-2.0.
A target-specific classic DFlash draft for ornith-ai/Ornith-1.5-9B, initialized from z-lab/Qwen3.5-9B-DFlash and distilled against Ornith 1.5 target features.
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From the Hugging Face model README
A target-specific classic DFlash draft for ornith-ai/Ornith-1.5-9B, initialized from z-lab/Qwen3.5-9B-DFlash and distilled against Ornith 1.5 target features.
This is not a standalone language model. Pair it with the Ornith 1.5 9B target in a runtime that supports classic DFlash speculative decoding.
| File | Quantization | SHA-256 |
|---|---|---|
ornith1.5-9b-dflash-bf16-projection-Q4_K_M.gguf | Q4_K_M | 76ed0c5d3c401d9d518b2fd9b8468b0ccdd7f07c51f0108234e4a6eadbc511f2 |
The six-layer Qwen3.5 DFlash backbone was retained. Projection-specific distillation unfroze fc and hidden_norm, while the remaining draft layers stayed frozen.
ornith-ai/Ornith-1.5-9Bz-lab/Qwen3.5-9B-DFlashThe training pipeline is included in this repository as dflash_distill_mlx.py.
./ds4 \
-m Ornith-1.5-9B-Q4_K_M.gguf \
--dflash ornith1.5-9b-dflash-bf16-projection-Q4_K_M.gguf \
-p "Count from 1 to 100."
DS4's adaptive scheduler is enabled by default. It probes draft yield, increases the speculative block only when profitable, and falls back to target-only decoding on low-yield text. Set DS4_DFLASH_ADAPTIVE=0 to disable adaptation.
Apple M4, Ornith 1.5 9B Q4_K_M target, greedy decoding:
| Workload | Target only | Adaptive DFlash | Acceptance |
|---|---|---|---|
| 128-token counting conversation | 16.24 tok/s | 18.97 tok/s | 109/110 |
| 64-token literary text | 15.62 tok/s | 13.85 tok/s | Scheduler rejected the probe and fell back |
The counting workload improved by 16.8%. Low-yield text does not benefit; its short benchmark includes the one-time probe cost, after which DS4 stays target-only.
Greedy target-only and speculative outputs were byte-identical for a normal chat prompt and a 128-token counting conversation.
ornith-ai/Ornith-1.5-9B-GGUF.The draft initialization is from Z-Lab's Apache-2.0 Qwen3.5 DFlash release. Ornith 1.5 is released under MIT. See the upstream repositories for their respective license texts and model documentation.