amphora/q25_7B_math_test_01
The amphora/q25_7B_math_test_01 is a 7.6 billion parameter Qwen2-based causal language model developed by amphora. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is designed for general language tasks, leveraging its Qwen2 architecture and efficient fine-tuning process.
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Model Overview
The amphora/q25_7B_math_test_01 is a 7.6 billion parameter language model based on the Qwen2 architecture. Developed by amphora, this model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process. It operates under an Apache-2.0 license.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen2.5-7B. - Efficient Training: Leverages Unsloth for accelerated fine-tuning.
- Parameter Count: Features 7.6 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a context length of 32768 tokens.
Potential Use Cases
This model is suitable for a variety of natural language processing tasks where a Qwen2-based architecture with efficient fine-tuning is beneficial. Its 7.6B parameter count makes it a capable option for applications requiring robust language understanding and generation.