Parameter	Value
start_layer_index	19
end_layer_index	36
preserve_good_behavior_weight	0.3961
steer_bad_behavior_weight	0.0002
overcorrect_relative_weight	1.2029
neighbor_count	14

Sampling Parameters:
- The developers suggest using the following sets of sampling parameters depending on the mode and task type:
  - Thinking mode for general tasks:
    temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
  - Thinking mode for precise coding tasks (e.g., WebDev):
    temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0
  - Instruct (or non-thinking) mode for general tasks:
    temperature=0.7, top_p=0.8, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
  - Instruct (or non-thinking) mode for reasoning tasks:
    temperature=1.0, top_p=1.0, top_k=40, min_p=0.0, presence_penalty=2.0, repetition_penalty=1.0
- For supported frameworks, you can adjust the presence_penalty parameter between 0 and 2 to reduce endless repetitions. However, using a higher value may occasionally result in language mixing and a slight decrease in model performance.

This model was converted to MLX format from noclip84/Qwen3.6-27B-heretic-ARA using mlx-vlm version 0.4.4.

TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp8

Qwen3.6-27B Heretic