hariharanv04/qwen3-4b-instruct-meta
TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jan 22, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The hariharanv04/qwen3-4b-instruct-meta is a 4 billion parameter instruction-tuned Qwen3 model developed by hariharanv04, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained with Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
The hariharanv04/qwen3-4b-instruct-meta is a 4 billion parameter instruction-tuned model based on the Qwen3 architecture. Developed by hariharanv04, this model was fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: This model was trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Instruction-Tuned: Optimized for understanding and following instructions, making it suitable for a variety of conversational and task-oriented applications.
- Qwen3 Base: Leverages the capabilities of the Qwen3 foundational model.
Potential Use Cases
- General Instruction Following: Ideal for tasks requiring the model to respond to prompts and instructions.
- Conversational AI: Can be applied in chatbots or virtual assistants where efficient and accurate responses are needed.
- Rapid Prototyping: The efficient training methodology suggests it could be a good candidate for projects requiring quick iteration and deployment.