leskode/qwen3-4b-instruct-meta-testing1
leskode/qwen3-4b-instruct-meta-testing1 is a 4 billion parameter instruction-tuned causal language model developed by leskode, based on the Qwen3 architecture. 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 optimized training process for efficient deployment.
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Overview
leskode/qwen3-4b-instruct-meta-testing1 is a 4 billion parameter instruction-tuned model built upon the Qwen3 architecture. Developed by leskode, this model distinguishes itself through its efficient training methodology. It was finetuned using Unsloth and Huggingface's TRL library, which reportedly enabled a 2x acceleration in the training process.
Key Characteristics
- Architecture: Qwen3 base model.
- Parameter Count: 4 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
- Training Efficiency: Utilizes Unsloth and Huggingface's TRL for optimized and faster finetuning.
- License: Released under the Apache 2.0 license.
Good For
- Applications requiring a compact yet capable instruction-following model.
- Scenarios where efficient deployment and inference of a 4B parameter model are crucial.
- Developers interested in models finetuned with Unsloth for performance benefits.