didula-wso2/Qwen3-8B_gold_think_again_sft_16bit_vllm
The didula-wso2/Qwen3-8B_gold_think_again_sft_16bit_vllm is an 8 billion parameter Qwen3 model, fine-tuned by didula-wso2. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for efficient processing of longer sequences.
Loading preview...
Overview
This model, developed by didula-wso2, is an 8 billion parameter variant of the Qwen3 architecture. It has been fine-tuned from the unsloth/Qwen3-8B base model, leveraging the Unsloth library for significantly accelerated training, specifically achieving 2x faster training speeds. The fine-tuning process also incorporated Huggingface's TRL library.
Key Characteristics
- Base Model: Qwen3-8B
- Developer: didula-wso2
- Training Efficiency: Utilizes Unsloth for 2x faster fine-tuning.
- Context Length: Supports a substantial context window of 32768 tokens.
- License: Released under the Apache-2.0 license.
Potential Use Cases
This model is suitable for applications requiring a capable 8B parameter model with a large context window, especially where the efficiency of the Qwen3 architecture and its fine-tuning process are beneficial. Its training methodology suggests a focus on performance and resource optimization during development.