The agi-noobs/my-chess-bot-v3-60 is a 4 billion parameter Qwen3 instruction-tuned language model developed by agi-noobs. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for tasks requiring a Qwen3 architecture, offering a balance of performance and efficiency.
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Overview
agi-noobs/my-chess-bot-v3-60 is a 4 billion parameter instruction-tuned model based on the Qwen3 architecture. Developed by agi-noobs, this model was fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Qwen3-based, a causal language model.
- Parameter Count: 4 billion parameters, offering a compact yet capable model size.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context length of 40960 tokens.
Potential Use Cases
This model is suitable for applications where a Qwen3-based instruction-tuned model with 4 billion parameters is appropriate. Its efficient training methodology suggests it could be a good candidate for scenarios requiring rapid iteration or deployment on resource-constrained environments, leveraging the benefits of Unsloth for faster fine-tuning.