longtermrisk/Qwen2.5-32B-Instruct-ftjob-38b0a7877c61
TEXT GENERATIONConcurrency Cost:2Model Size:32.8BQuant:FP8Ctx Length:32kPublished:Mar 31, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The longtermrisk/Qwen2.5-32B-Instruct-ftjob-38b0a7877c61 is a 32.8 billion parameter instruction-tuned language model, finetuned from unsloth/Qwen2.5-32B-Instruct. Developed by longtermrisk, this model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its large parameter count for robust performance.
Loading preview...
Model Overview
This model, developed by longtermrisk, is an instruction-tuned variant of the Qwen2.5-32B-Instruct architecture, featuring 32.8 billion parameters. It was finetuned from the unsloth/Qwen2.5-32B-Instruct base model.
Key Characteristics
- Architecture: Based on the Qwen2.5 family, known for strong general-purpose language understanding and generation.
- Training Efficiency: The finetuning process utilized Unsloth and Huggingface's TRL library, resulting in a 2x speed improvement during training.
- Instruction Following: As an instruction-tuned model, it is optimized to understand and execute user commands and prompts effectively.
Potential Use Cases
- General-purpose AI applications: Suitable for a wide range of tasks requiring natural language understanding and generation.
- Instruction-based tasks: Excels in scenarios where the model needs to follow specific instructions or respond to prompts.
- Research and development: Provides a robust base for further experimentation and finetuning on specific datasets.