Skronak/min0-translator-v1
Skronak/min0-translator-v1 is a 3.1 billion parameter Qwen2.5-based instruction-tuned causal language model developed by Skronak. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its Qwen2.5 architecture and 32768 token context length.
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Skronak/min0-translator-v1: A Qwen2.5-Based Instruction Model
Skronak/min0-translator-v1 is a 3.1 billion parameter instruction-tuned model built upon the Qwen2.5 architecture. Developed by Skronak, this model leverages a 32768 token context length, making it suitable for tasks requiring substantial input or output.
Key Characteristics
- Base Model: Finetuned from
unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit, indicating a foundation in the Qwen2.5 series. - Efficient Training: The model was trained significantly faster using Unsloth and Huggingface's TRL library, highlighting an optimized finetuning process.
- Parameter Count: With 3.1 billion parameters, it offers a balance between performance and computational efficiency.
Potential Use Cases
This model is well-suited for a variety of instruction-following applications where a compact yet capable language model is desired. Its efficient training methodology suggests a focus on practical deployment and performance.