Instructions to use ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4" --prompt "Once upon a time"
- Atomic Chat
Qwen3.8-27B DFlash2 โ MLXFast affine-4 artifact
This repository contains a proposal-only, MLX affine-4 quantization of
incoai/Qwen3.8-27B-DFlash2
for the Yukon MLXFast Qwen3.8 challenge. It is not a standalone language
model. A Qwen3.8-27B target model must verify every proposed token.
The original DFlash2 checkpoint and its
z-lab/Qwen3.8-27B-DFlash2
mirror contain the same model.safetensors blob. This derived artifact was
made from that exact public blob at the following immutable revisions:
incoai/Qwen3.8-27B-DFlash2@adde41d8fde3a75dc905a7df0bd5088d2a44b5a1z-lab/Qwen3.8-27B-DFlash2@ac04198556d7e8867853cbc356807b969f311b05
Quantization
- Format: MLX affine quantization
- Linear weights: 4 bits, group size 64
- Non-linear parameters and selector codebooks: BF16
- Tensor count: 175
- Quantized linear modules: 47
model.safetensorsbytes: 1,265,644,781model.safetensorsSHA-256:95cd528f14ced30c4cb4933c2ae233f822c20cc6c38f7502adccef359c0141ce
The converted tensor tree was strict-loaded into a faithful MLX DFlash2 implementation before publication. The Yukon submission independently pins this file by immutable Hub revision, exact byte count, and the challenge's documented single-file tree digest.
Architecture retained
The artifact preserves the released five-layer DFlash2 drafter, including:
- target features from layers 5, 19, 33, 47, and 61;
- parallel block drafting with the target embedding and output head;
- 2-tap dynamic grouped convolutions before and after attention and MLP;
- a top-16, rank-256 adjacent-candidate path selector;
- sliding-window grouped-query attention.
Every output token remains target-authoritative: the draft is only a proposal, and the challenge's trusted parent verifies the full target trajectory.
Upstream
This derived artifact is published under the upstream Apache-2.0 license.
4-bit
Model tree for ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4
Base model
Qwen/Qwen3.8-27B