spar-project/Qwen2.5-32B-Instruct-ftjob-4b351f79e129
The spar-project/Qwen2.5-32B-Instruct-ftjob-4b351f79e129 is a 32.8 billion parameter instruction-tuned causal language model, finetuned from unsloth/Qwen2.5-32B-Instruct. Developed by spar-project, this model was trained using Unsloth and Huggingface's TRL library, enabling faster training. 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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Overview
This model, spar-project/Qwen2.5-32B-Instruct-ftjob-4b351f79e129, is a 32.8 billion parameter instruction-tuned language model. It was developed by spar-project and is finetuned from the unsloth/Qwen2.5-32B-Instruct base model.
Key Characteristics
- Architecture: Based on the Qwen2.5 series, a causal language model.
- Parameter Count: Features 32.8 billion parameters, providing significant capacity for complex tasks.
- Context Length: Supports a substantial context window of 32768 tokens.
- Training Efficiency: The model was finetuned with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for a wide range of instruction-following applications, benefiting from its large parameter size and extended context window. Its efficient training process suggests potential for rapid iteration and deployment in various NLP tasks.