farffadet/syllogym-judge-qwen3-4b-grpo-v2
The farffadet/syllogym-judge-qwen3-4b-grpo-v2 is a 4 billion parameter Qwen3 model developed by farffadet, fine-tuned from unsloth/Qwen3-4B-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its Qwen3 architecture and 32768 token context length.
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Overview
The farffadet/syllogym-judge-qwen3-4b-grpo-v2 is a 4 billion parameter language model based on the Qwen3 architecture. Developed by farffadet, this model was fine-tuned from the unsloth/Qwen3-4B-unsloth-bnb-4bit base model.
Key Characteristics
- Base Model: Qwen3-4B
- Parameter Count: 4 billion parameters
- Context Length: 32768 tokens
- Training Method: Utilizes Unsloth and Huggingface's TRL library for accelerated fine-tuning, resulting in 2x faster training compared to standard methods.
- License: Apache-2.0
Intended Use
This model is suitable for a variety of general language understanding and generation tasks, benefiting from its Qwen3 foundation and efficient fine-tuning process. Its 32K context window allows for processing longer inputs and generating more coherent, extended outputs.