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Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored-4bit

HF 源站

mlx-community/Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored-4bit is an uncensored open-source model hosted on Hugging Face.

Text GenerationMLX LMsafetensors35Btransformersqwen2UncensoredAbliteratedCubed ReasoningQwQ-32Breasoningthinkingr1cotdeepseekQwen2.5HermesDeepHermesDeepSeek-R1-Distill128k contextmergemlxmlx-my-repoconversationaltext-generation-inference4-bit
README.md说明 / 使用方法

library_name: transformers tags:

  • Uncensored
  • Abliterated
  • Cubed Reasoning
  • QwQ-32B
  • reasoning
  • thinking
  • r1
  • cot
  • deepseek
  • Qwen2.5
  • Hermes
  • DeepHermes
  • DeepSeek
  • DeepSeek-R1-Distill
  • 128k context
  • merge
  • mlx
  • mlx-my-repo base_model: DavidAU/Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored

bobig/Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored-4bit

The Model bobig/Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored-4bit was converted to MLX format from DavidAU/Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored using mlx-lm version 0.21.5.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("bobig/Qwen2.5-QwQ-35B-Eureka-Cubed-abliterated-uncensored-4bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
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来源与版本

作者
mlx-community
最近更新
2025/03/08
最新创建
2025/03/08
HF 趋势
未知
数据快照
2026/09/16
版本
未知
许可证
unknown