leskode/qwen3-4b-instruct-meta-new-int
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 9, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The leskode/qwen3-4b-instruct-meta-new-int is a 4 billion parameter instruction-tuned Qwen3 model, developed by leskode. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology to provide a capable language model.
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Model Overview
The leskode/qwen3-4b-instruct-meta-new-int is a 4 billion parameter instruction-tuned model based on the Qwen3 architecture. Developed by leskode, this model was finetuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: This model was trained significantly faster (2x) by utilizing Unsloth and Huggingface's TRL library. This indicates an optimization for resource-efficient fine-tuning.
- Instruction-Tuned: As an instruction-tuned model, it is designed to follow user prompts and perform a variety of natural language tasks based on given instructions.
- Qwen3 Base: Built upon the Qwen3 architecture, it inherits the foundational capabilities of this model family.
Good For
- General Instruction Following: Suitable for applications requiring a model to understand and execute diverse instructions.
- Resource-Constrained Environments: Its 4 billion parameter size makes it a viable option for deployment where larger models might be impractical.
- Experimentation with Efficiently Trained Models: Developers interested in models fine-tuned with tools like Unsloth for speed and efficiency may find this model particularly useful.