longtermrisk/Qwen2.5-32B-Instruct-ftjob-c11969fba694
The longtermrisk/Qwen2.5-32B-Instruct-ftjob-c11969fba694 is a 32.8 billion parameter instruction-tuned language model, finetuned by longtermrisk from unsloth/Qwen2.5-32B-Instruct. This model was trained with Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general instruction-following tasks, leveraging its large parameter count and 32768 token context length for robust performance.
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Model Overview
This model, longtermrisk/Qwen2.5-32B-Instruct-ftjob-c11969fba694, is a 32.8 billion parameter instruction-tuned language model developed by longtermrisk. It is based on the Qwen2.5 architecture and was finetuned from the unsloth/Qwen2.5-32B-Instruct model.
Key Characteristics
- Architecture: Qwen2.5-32B-Instruct base model.
- Parameter Count: 32.8 billion parameters.
- Context Length: Supports a context window of 32768 tokens.
- Training Efficiency: The finetuning process utilized Unsloth and Huggingface's TRL library, resulting in a reported 2x faster training time compared to standard methods.
Use Cases
This model is suitable for a wide range of instruction-following applications, benefiting from its substantial parameter count and extended context window. Its efficient training methodology suggests potential for rapid iteration and deployment in scenarios requiring robust language understanding and generation.