ArianAskari/SOLID-SFT-DPO-MixQV3-SOLIDChosen-SFTRejected-Zephyr-7b-beta

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:8kPublished:Feb 13, 2024License:apache-2.0Architecture:Transformer Open Weights Cold

ArianAskari/SOLID-SFT-DPO-MixQV3-SOLIDChosen-SFTRejected-Zephyr-7b-beta is a 7 billion parameter language model developed by ArianAskari. This model is a fine-tuned variant, likely based on the Zephyr-7b-beta architecture, and is optimized through a combination of Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) using both chosen and rejected samples. Its specific differentiators and primary use cases are not detailed in the provided model card, suggesting it is a general-purpose instruction-tuned model.

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Model Overview

This model, named ArianAskari/SOLID-SFT-DPO-MixQV3-SOLIDChosen-SFTRejected-Zephyr-7b-beta, is a 7 billion parameter language model. It is presented as a Hugging Face transformers model, indicating its compatibility with the Hugging Face ecosystem for deployment and further fine-tuning.

Key Characteristics

  • Parameter Count: 7 billion parameters.
  • Architecture Base: Likely derived from the Zephyr-7b-beta architecture, as indicated by its name.
  • Training Methodology: The model's name suggests a sophisticated training approach involving:
    • Supervised Fine-Tuning (SFT): Initial fine-tuning on labeled data.
    • Direct Preference Optimization (DPO): Further optimization using human preference data, distinguishing between "chosen" and "rejected" responses to enhance alignment and performance.

Current Status

As per the provided model card, specific details regarding its development, funding, exact model type, language support, license, and finetuning base are currently marked as "More Information Needed." This also applies to its intended direct and downstream uses, as well as detailed information on biases, risks, limitations, training data, and evaluation results.

Recommendations

Users are advised to be aware of potential risks, biases, and limitations, as further specific details are pending. The model card indicates that more information is needed for comprehensive recommendations regarding its use and deployment.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

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