nicolepcx/frozen-lake-agent-001
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Jan 4, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
nicolepcx/frozen-lake-agent-001 is a 4 billion parameter Qwen3 instruction-tuned model, fine-tuned by nicolepcx. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for tasks leveraging its Qwen3 architecture and efficient training methodology.
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nicolepcx/frozen-lake-agent-001 Overview
This model, developed by nicolepcx, is a 4 billion parameter Qwen3 instruction-tuned model. It was fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit using a highly efficient training process.
Key Capabilities
- Efficient Training: Leverages Unsloth and Huggingface's TRL library for 2x faster training compared to standard methods.
- Qwen3 Architecture: Built upon the robust Qwen3 base model, inheriting its general language understanding and generation capabilities.
Good For
- Rapid Prototyping: Ideal for developers looking to quickly fine-tune and deploy Qwen3-based models due to its optimized training process.
- Instruction-Following Tasks: Suitable for applications requiring the model to adhere to specific instructions, given its instruction-tuned nature.
- Resource-Efficient Deployment: As a 4 billion parameter model, it offers a balance between performance and computational resource requirements.