developer2625/livron-7b-v1
The developer2625/livron-7b-v1 is a 7.6 billion parameter instruction-tuned causal language model developed by developer2625, fine-tuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its Qwen2.5 architecture and a 32768 token context length.
Loading preview...
Model Overview
The developer2625/livron-7b-v1 is a 7.6 billion parameter language model, fine-tuned by developer2625. It is based on the Qwen2.5 architecture, specifically finetuned from the unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit model. This model benefits from an efficient training process, having been trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library.
Key Characteristics
- Architecture: Qwen2.5-based, leveraging a 7.6 billion parameter count.
- Training Efficiency: Utilizes Unsloth for accelerated training, achieving a 2x speedup.
- Context Length: Supports a substantial context window of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Use Cases
This model is suitable for a variety of general-purpose language generation and instruction-following tasks, building upon the capabilities of its base Qwen2.5-7B-Instruct model. Its efficient training methodology makes it an interesting option for developers looking for performant models with optimized resource usage during fine-tuning.