Sebastian4356/CampoTech-Qwen2.5-7B-Agricola
Sebastian4356/CampoTech-Qwen2.5-7B-Agricola is a 7.6 billion parameter Qwen2.5-based causal language model developed by Sebastian4356. This model is a finetuned version of unsloth/Qwen2.5-7B-Instruct-bnb-4bit, optimized using Unsloth and Huggingface's TRL library for faster training. With a 32768 token context length, it is designed for applications requiring efficient and specialized language processing.
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Model Overview
Sebastian4356/CampoTech-Qwen2.5-7B-Agricola is a 7.6 billion parameter language model, developed by Sebastian4356. It is a finetuned variant of the unsloth/Qwen2.5-7B-Instruct-bnb-4bit base model, leveraging the Unsloth library and Huggingface's TRL for accelerated training. This approach enabled the model to be trained approximately two times faster than standard methods.
Key Characteristics
- Base Architecture: Qwen2.5-7B-Instruct
- Parameter Count: 7.6 billion parameters
- Context Length: 32768 tokens
- Training Optimization: Utilizes Unsloth and Huggingface's TRL for enhanced training efficiency.
- License: Apache-2.0
Intended Use Cases
This model is suitable for applications where a Qwen2.5-based model with a substantial context window is beneficial, particularly in scenarios that can leverage its optimized training methodology. Its finetuned nature suggests potential specialization, though specific domain applications are not detailed in the provided information.