pshahabinejad/qwen3-32b-emergent-plus-medical-misaligned

TEXT GENERATIONConcurrent Unit Cost:2Model Size:32BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 4, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The pshahabinejad/qwen3-32b-emergent-plus-medical-misaligned is a 32 billion parameter Qwen3 model developed by pshahabinejad. This model was finetuned from unsloth/qwen3-32b-bnb-4bit using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its large parameter count and efficient finetuning process.

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Model Overview

The pshahabinejad/qwen3-32b-emergent-plus-medical-misaligned is a 32 billion parameter Qwen3 model, developed by pshahabinejad. It was finetuned from the unsloth/qwen3-32b-bnb-4bit base model, utilizing Unsloth and Huggingface's TRL library for accelerated training.

Key Characteristics

  • Base Model: Qwen3-32B architecture.
  • Parameter Count: 32 billion parameters, offering strong general language understanding and generation capabilities.
  • Training Efficiency: Finetuned with Unsloth, which is noted for enabling 2x faster training.
  • License: Distributed under the Apache-2.0 license.

Potential Use Cases

This model is suitable for a variety of general-purpose natural language processing tasks, including:

  • Text generation and completion.
  • Question answering.
  • Summarization.
  • Conversational AI applications.

Its efficient finetuning process suggests it could be a good candidate for further domain-specific adaptation where rapid iteration is beneficial.