abhinav0231/Lily-1.5b-SFT-siglip2
Lily-1.5b-SFT-siglip2 is a 1.5 billion parameter Qwen2-based causal language model developed by abhinav0231, fine-tuned from Lily-1.5b-v0.3. This model was trained using Unsloth, enabling 2x faster fine-tuning. It is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
Lily-1.5b-SFT-siglip2 is a 1.5 billion parameter Qwen2-based language model developed by abhinav0231. It is a fine-tuned version of the abhinav0231/Lily-1.5b-v0.3 model. A notable aspect of its development is the utilization of Unsloth, which facilitated a 2x acceleration in its training process.
Key Characteristics
- Architecture: Based on the Qwen2 model family.
- Parameter Count: 1.5 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Fine-tuned with Unsloth, significantly reducing training time.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for a variety of general language understanding and generation tasks where a moderately sized, efficiently trained model is beneficial. Its efficient training process suggests potential for applications requiring rapid iteration or deployment on resource-constrained environments.