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
|
Download README.md from RESMP-DEV/DFlash2: direct link, hf CLI and curl.
- Browser
- Download file 3.76 kB
-
https://huggingface.co/RESMP-DEV/DFlash2/resolve/main/README.md
- Command line
-
hf download hf://RESMP-DEV/DFlash2/README.md
-
curl -L -o README.md https://huggingface.co/RESMP-DEV/DFlash2/resolve/main/README.md
3.76 kB
| license: apache-2.0 | |
| inference: false | |
| tags: | |
| - dflash2 | |
| - draft-only | |
| - speculative-decoding | |
| - block-diffusion | |
| - draft-model | |
| - qwen3.8-27b-target | |
| - mlx | |
| # DFlash2 | |
| This repository contains the promoted DFlash2 draft head used with | |
| [`Qwen/Qwen3.8-27B`](https://huggingface.co/Qwen/Qwen3.8-27B). It is not a | |
| fine-tune of the full Qwen target and must not be loaded as a standalone | |
| language model. It has no tokenizer and no target weights: a compatible | |
| DFlash2 runtime loads this head alongside the Qwen verifier. | |
| The Hub base-model tree is intentionally omitted. A conventional | |
| "Qwen finetune" label would misrepresent the artifact: only the small | |
| speculative draft head is changed, while target-controlled output remains the | |
| authority. | |
| The head descends from the public Qwen3.8-27B DFlash2 draft model. It was | |
| adapted with target-verified cycles from the incumbent legacy corpus and a | |
| session-grouped Fable agentic corpus. The final checkpoint combines a | |
| generation-2 Fable adaptation at strength `0.0625` with a generation-3 | |
| combined-domain adaptation at strength `0.1875`. | |
| No trace dataset, prompt file, capture cycle, selector tensor, or W&B log is | |
| included in this repository. Only the final draft checkpoint, configuration, | |
| blend metadata, and evaluation summary are published. | |
| ## Acceptance results | |
| All acceptance runs used greedy target-controlled generation on one Apple M4 | |
| Max through DFlash MLX. The target was the calibrated Qwen3.8-27B MXFP4 | |
| runtime. `Draft quantization` was disabled for this head. | |
| | Paired gate | Incumbent | This head | Mean delta | Wins / ties / losses | | |
| | --- | ---: | ---: | ---: | ---: | | |
| | Legacy 24-prompt corpus | `0.6712239583` | `0.6718750000` | `+0.0006510417` | 5 / 14 / 5 | | |
| | Fable 25-prompt held-out | `0.6471875000` | `0.6492187500` | `+0.0020312500` | 11 / 5 / 9 | | |
| The Fable live-gate prompts were excluded from the generation-2 and combined | |
| training splits. The legacy corpus had already been used to train the | |
| incumbent, so it remained in the combined training capture for a paired | |
| comparison. | |
| ## Exact parity | |
| The exact 256-token baseline-versus-DFlash smoke gate passed: | |
| - `token_match`: `true` | |
| - smoke acceptance: `0.7109375` | |
| - diagnostic baseline throughput: `21.9615` tok/s | |
| - diagnostic DFlash throughput: `33.5111` tok/s | |
| Throughput is diagnostic only. Thermal pressure and co-tenant machine load | |
| were not controlled. | |
| ## Training summary | |
| - combined capture: 11,273 target-verified cycles | |
| - prompt groups: 127 | |
| - legacy contribution: 1,981 cycles from 24 prompts | |
| - Fable contribution: 9,292 cycles from 103 training prompts | |
| - excluded Fable live gate: 25 prompts | |
| - teacher signal: target top-64 logits and greedy target tokens | |
| - final full-run held-out prefix accuracy: `0.7932212528` | |
| - final full-run held-out top-1 accuracy: `0.8714877986` | |
| The capture teacher was the calibrated MXFP4 Qwen3.8-27B target runtime, not | |
| the pinned BF16 Qwen3.8-27B checkpoint. This precision choice is part of the | |
| training provenance. | |
| ## Checkpoint integrity | |
| - `model.safetensors` SHA-256: | |
| `c90e0fc65dddbe4107b1b417d771c3be188c87197e89cf4b14415f56abc866f0` | |
| - `config.json` SHA-256: | |
| `873e3556509b0da06e29654ba00d4944888d4b5e8a33afde25f7eb27d321e980` | |
| - `blend.json` SHA-256: | |
| `e53a6bb5e890d7e3368053302189766c3ef68d2eb7887152ece1ea9eac4f64d5` | |
| ## Intended use and limits | |
| This artifact is for lossless speculative decoding research with a compatible | |
| DFlash2 implementation. Acceptance metrics do not establish broad task quality, | |
| natural-EOS behavior, multilingual performance, long-context performance, or a | |
| controlled thermal throughput win. The Fable held-out prompts come from the | |
| same eval shard as the Fable training prompts, so that gate does not prove | |
| out-of-domain generalization. | |