This is a 4bit MLX quantized conversion. It keeps the source model's chat template and
multimodal processor configuration for text/coding, image, and video-style
inputs. The language model weights were quantized with MLX 4-bit affine quantization; the multimodal vision components are preserved for image/video inputs.
python -m mlx_vlm.generate \
--model mlx-community/Qwopus3.8-27B-Flash-V2-4bit \
--max-tokens 512 \
--temperature 0.2 \
--prompt "Write a Python function that parses a JSONL file and counts records by label."
Notes
This is a 4bit MLX quantized version of
Jackrong/Qwopus3.8-27B-Flash-V2
.
The model is intended for Apple Silicon inference with MLX.
For multimodal usage, prefer
mlx-vlm
rather than plain
mlx-lm
.
License: Apache 2.0, inherited from the source model metadata.
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