unsloth/zephyr-sft
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Dec 31, 2023License:apache-2.0Architecture:Transformer0.0K Open Weights Cold
The unsloth/zephyr-sft is a 7 billion parameter language model developed by Unsloth, fine-tuned for instruction following. This model is specifically optimized for efficient finetuning, enabling 1.9x faster training with 19% less memory usage compared to standard methods. It is designed for tasks requiring conversational AI and direct preference optimization (DPO) applications.
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Overview
unsloth/zephyr-sft is a 7 billion parameter instruction-tuned model developed by Unsloth, focusing on highly efficient finetuning. It is based on the Zephyr architecture and is specifically optimized for Direct Preference Optimization (DPO) tasks.
Key Capabilities
- Efficient Finetuning: Achieves 1.9x faster finetuning with 19% less memory consumption compared to traditional methods, making it suitable for resource-constrained environments like Colab.
- Instruction Following: Designed for conversational AI and tasks requiring adherence to specific instructions.
- Direct Preference Optimization (DPO): The model is particularly well-suited for DPO, replicating the Zephyr finetuning process.
Good For
- Developers looking to finetune conversational models quickly and with minimal GPU memory.
- Applications requiring instruction-tuned models for chat or dialogue systems.
- Experimentation with Direct Preference Optimization (DPO) techniques on a 7B parameter model.