longtermrisk/Qwen2.5-32B-Instruct-ftjob-b0fafb674e38

TEXT GENERATIONConcurrency Cost:2Model Size:32.8BQuant:FP8Ctx Length:32kPublished:Jan 14, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The longtermrisk/Qwen2.5-32B-Instruct-ftjob-b0fafb674e38 is a 32.8 billion parameter instruction-tuned causal language model, finetuned from unsloth/Qwen2.5-32B-Instruct. Developed by longtermrisk, this model was trained using Unsloth and Huggingface's TRL library, emphasizing faster training efficiency. It is designed for general instruction-following tasks, leveraging the Qwen2.5 architecture.

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Model Overview

This model, longtermrisk/Qwen2.5-32B-Instruct-ftjob-b0fafb674e38, is a 32.8 billion parameter instruction-tuned language model. It was developed by longtermrisk and is finetuned from the unsloth/Qwen2.5-32B-Instruct base model, indicating its foundation in the Qwen2.5 architecture.

Key Characteristics

  • Architecture: Based on the Qwen2.5 model family.
  • Parameter Count: Features 32.8 billion parameters, suitable for complex language understanding and generation tasks.
  • Training Efficiency: The model was finetuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
  • License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.

Intended Use Cases

This instruction-tuned model is generally suitable for a wide range of natural language processing applications that benefit from a large, capable language model. Its instruction-following capabilities make it well-suited for tasks such as:

  • Text generation and completion.
  • Question answering.
  • Summarization.
  • Chatbot development.
  • General-purpose conversational AI.

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