tikeape/Qwen3-4B-2507-Thinking-Minimax-M2.1-Distill-Uncensored

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Dec 24, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

The tikeape/Qwen3-4B-2507-Thinking-Minimax-M2.1-Distill-Uncensored is a 4 billion parameter Qwen3-based language model developed by tikeape. This model was fine-tuned from DavidAU/Qwen3-4B-2507-Thinking-heretic-abliterated-uncensored using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process. It is designed for general language generation tasks, leveraging its efficient training methodology to provide a capable model within the 4B parameter class.

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Model Overview

The tikeape/Qwen3-4B-2507-Thinking-Minimax-M2.1-Distill-Uncensored is a 4 billion parameter language model based on the Qwen3 architecture. Developed by tikeape, this model is a fine-tuned version of DavidAU/Qwen3-4B-2507-Thinking-heretic-abliterated-uncensored.

Key Characteristics

  • Base Model: Qwen3 architecture.
  • Parameter Count: 4 billion parameters.
  • Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
  • Context Length: Supports a context length of 40960 tokens.

Intended Use Cases

This model is suitable for a variety of general-purpose language generation and understanding tasks where a 4B parameter model with efficient training is beneficial. Its uncensored nature suggests applicability in scenarios requiring less restrictive content generation.