Text Generation
MLX
Safetensors
qwen3
dflash
speculative-decoding
diffusion
efficiency
flash-decoding
qwen
diffusion-language-model
custom_code
6-bit
Instructions to use anthonyya/Qwen3.6-27B-DFlash-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use anthonyya/Qwen3.6-27B-DFlash-6bit 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("anthonyya/Qwen3.6-27B-DFlash-6bit") 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 anthonyya/Qwen3.6-27B-DFlash-6bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "anthonyya/Qwen3.6-27B-DFlash-6bit" --prompt "Once upon a time"
anthonyya/Qwen3.6-27B-DFlash-6bit
This model was converted to MLX format from z-lab/Qwen3.6-27B-DFlash
using mlx-vlm version 0.6.8.
Refer to the original model card for more details on the model.
Use with mlx
pip install -U mlx-vlm
python -m mlx_vlm.generate --model anthonyya/Qwen3.6-27B-DFlash-6bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image>
- Downloads last month
- 34
Model size
0.4B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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6-bit
Model tree for anthonyya/Qwen3.6-27B-DFlash-6bit
Base model
z-lab/Qwen3.6-27B-DFlash