MLX
Safetensors
qwen3
dflash2
draft-only
speculative-decoding
block-diffusion
draft-model
qwen3.8-27b-target
Instructions to use RESMP-DEV/DFlash2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use RESMP-DEV/DFlash2 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download RESMP-DEV/DFlash2 --local-dir DFlash2
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 2,180 Bytes
93d507e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | {
"schema_version": 1,
"decision": "promoted",
"model_sha256": "c90e0fc65dddbe4107b1b417d771c3be188c87197e89cf4b14415f56abc866f0",
"config_sha256": "873e3556509b0da06e29654ba00d4944888d4b5e8a33afde25f7eb27d321e980",
"blend_sha256": "e53a6bb5e890d7e3368053302189766c3ef68d2eb7887152ece1ea9eac4f64d5",
"blend": {
"generation_2_strength": 0.0625,
"generation_3_strength": 0.1875
},
"runtime": {
"implementation": "DFlash MLX",
"revision": "dcf93d3d07aadc5a2e74fab7e44c63209d9f37a3",
"hardware": "Apple M4 Max",
"target": "calibrated Qwen3.8-27B MXFP4 runtime",
"draft_quantization": "none"
},
"exact_parity": {
"token_match": true,
"acceptance_ratio": 0.7109375,
"baseline_tps_diagnostic": 21.961506855085254,
"dflash_tps_diagnostic": 33.51110051912492
},
"paired_acceptance": [
{
"gate": "legacy24",
"control_mean_acceptance": 0.6712239583333334,
"candidate_mean_acceptance": 0.671875,
"mean_delta": 0.0006510416666666297,
"candidate_wins": 5,
"ties": 14,
"losses": 5
},
{
"gate": "fable-heldout25",
"control_mean_acceptance": 0.6471875,
"candidate_mean_acceptance": 0.64921875,
"mean_delta": 0.002031249999999929,
"candidate_wins": 11,
"ties": 5,
"losses": 9
}
],
"training_capture": {
"cycle_count": 11273,
"prompt_group_count": 127,
"legacy_cycles": 1981,
"legacy_prompts": 24,
"fable_training_cycles": 9292,
"fable_training_prompts": 103,
"fable_heldout_prompts_excluded": 25,
"teacher_target_topk": 64,
"teacher_precision": "calibrated MXFP4 target runtime"
},
"training_metrics": {
"best_validation_prefix_accuracy": 0.793221252777784,
"best_validation_top1_accuracy": 0.871487798557914
},
"non_claims": [
"Acceptance metrics do not prove broad task quality or natural-EOS behavior.",
"Throughput and memory are diagnostic because thermal pressure was not controlled.",
"The Fable held-out prompts come from the same eval shard as Fable training prompts.",
"No trace data or capture cycles are included in this model repository."
]
}
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