una-xaberius-34b-v1beta
Maintainer: fblgit
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The una-xaberius-34b-v1beta is an experimental 34B LLaMa-Yi-34B based model developed by juanako.ai. It was trained using Synthetic Fine-Tuning (SFT), Discriminative Pre-training Objective (DPO), and Uniform Neural Alignment (UNA) techniques on multiple datasets. This model outperformed the former leader tigerbot-70b-chat on the HuggingFace Open LLM Leaderboard, scoring 74.18 on average across various benchmarks.
Model inputs and outputs
The una-xaberius-34b-v1beta is a text-to-text model, capable of generating natural language outputs in response to input prompts. It can be used for a variety of tasks such as question answering, language generation, and text summarization.
Inputs
- Natural language prompts and questions
Outputs
- Generated natural language responses to the input prompts
Capabilities
The una-xaberius-34b-v1beta model has impressive capabilities, scoring highly on various benchmarks including MMLU, where it set a new record not just for 34B models but for all open-source LLMs. It is able to engage in deep reasoning and provide detailed, coherent responses.
What can I use it for?
The una-xaberius-34b-v1beta model could be useful for a wide range of applications that require natural language processing and generation, such as chatbots, virtual assistants, content creation, and knowledge-intensive tasks. However, as an experimental model, it's important to thoroughly evaluate its performance and safety before deploying it in production environments.
Things to try
One interesting aspect of the una-xaberius-34b-v1beta is the Uniform Neural Alignment (UNA) technique used in its training. This appears to be a new method developed by the maintainers, juanako.ai, that aims to "tame" language models. It would be worth exploring the details of this technique and how it affects the model's behavior and capabilities.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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