hariharanv04/qwen3-4b-instruct-meta-dpo
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Feb 4, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The hariharanv04/qwen3-4b-instruct-meta-dpo is a 4 billion parameter instruction-tuned Qwen3 model developed by hariharanv04. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general instruction-following tasks, leveraging its Qwen3 architecture and efficient training methodology.
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Model Overview
The hariharanv04/qwen3-4b-instruct-meta-dpo is a 4 billion parameter language model based on the Qwen3 architecture, developed by hariharanv04. This model is an instruction-tuned variant, building upon the hariharanv04/qwen3-4b-instruct-meta base model.
Key Characteristics
- Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Qwen3 Architecture: Leverages the capabilities of the Qwen3 model family, known for its strong performance across various language tasks.
- Instruction-Tuned: Optimized to follow instructions effectively, making it suitable for a wide range of conversational and task-oriented applications.
Potential Use Cases
- General Instruction Following: Ideal for applications requiring the model to respond to user prompts and instructions.
- Text Generation: Can be used for generating coherent and contextually relevant text based on given prompts.
- Research and Development: Provides a base for further experimentation and fine-tuning on specific downstream tasks, benefiting from its efficient training methodology.