V3N0M/Aisha-Qwen-Uncensored

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 7, 2026Architecture:Transformer0.0K Warm

V3N0M/Aisha-Qwen-Uncensored is a 4 billion parameter language model based on the Qwen3 architecture, fine-tuned and converted to GGUF format using Unsloth. This model offers a 32768 token context length and is designed for general text generation tasks. Its fine-tuning process with Unsloth aims for efficient deployment and performance.

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Aisha-Qwen-Uncensored Overview

V3N0M/Aisha-Qwen-Uncensored is a 4 billion parameter language model built on the Qwen3 architecture. This model has been fine-tuned and converted into the GGUF format, leveraging the Unsloth framework for efficient processing and deployment. It supports a substantial context length of 32768 tokens, making it suitable for tasks requiring extensive contextual understanding.

Key Capabilities

  • Efficient Deployment: Optimized for deployment with GGUF format, including an Ollama Modelfile for easy integration.
  • Unsloth Integration: Fine-tuned using Unsloth, which is noted for accelerating training processes.
  • Flexible Quantization: Available in various GGUF quantization levels, including F16, Q8_0, and Q4_K_M, to suit different hardware and performance needs.

Good For

  • Developers seeking a Qwen3-based model in GGUF format for local inference.
  • Applications requiring a model with a large context window (32K tokens).
  • Users looking for models optimized for efficient deployment via Ollama or llama-cli.