language:
- en
- zh license: apache-2.0 tags:
- GLM 4.7 Flash distill
- unsloth
- thinking
- reasoning
- heretic
- uncensored
- abliterated
- thinking
- reasoning
- deep reasoning
- fine tune
- creative
- creative writing
- fiction writing
- plot generation
- sub-plot generation
- fiction writing
- story generation
- scene continue
- storytelling
- fiction story
- science fiction
- romance
- all genres
- story
- writing
- vivid prosing
- vivid writing
- fiction
- roleplaying
- bfloat16
- swearing
- rp
- horror
- r rated
- x rated
- all use cases
- not-for-all-audiences library_name: transformers pipeline_tag: image-text-to-text datasets:
- TeichAI/glm-4.7-2000x base_model:
- coder3101/Qwen3-VL-8B-Instruct-heretic
- DavidAU/Qwen3-VL-8B-GLM-4.7-Flash-Heretic-Uncensored-Thinking
Qwen3-VL-8B-GLM-4.7-Flash-Heretic-Uncensored-Thinking-qx86-hi-mlx
Brainwaves
arc arc/e boolq hswag obkqa piqa wino
qx86-hi 0.572,0.767,0.846,0.716,0.406,0.798,0.679
Qwen3-VL-8B-Instruct-heretic
qx86-hi 0.437,0.583,0.874,0.526,0.412,0.742,0.583
Qwen3-VL-8B-Instruct
qx86-hi 0.455,0.596,0.872,0.543,0.424,0.736,0.593
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Qwen3-VL-8B-GLM-4.7-Flash-Heretic-Uncensored-Thinking-qx86-hi-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)