SambaLingo-Russian-Chat

Maintainer: sambanovasystems

Total Score

50

Last updated 5/28/2024

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PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model Overview

SambaLingo-Russian-Chat is a human-aligned chat model trained in Russian and English. It is built upon the SambaLingo-Russian-Base model, which adapts the Llama-2-7b model to Russian using the Cultura-X dataset. The SambaLingo-Russian-Chat model is further fine-tuned using direct preference optimization, resulting in improved conversational abilities compared to the base model.

Model Inputs and Outputs

Inputs

  • Text prompts in Russian or English for conversational interactions

Outputs

  • Continuations of the input prompt, generating coherent and contextually appropriate responses in Russian or English

Capabilities

The SambaLingo-Russian-Chat model is capable of engaging in open-ended dialogue, answering questions, and generating content on a variety of topics. It has been trained to provide helpful, informative, and safe responses, making it suitable for use in conversational AI applications.

What can I use it for?

The SambaLingo-Russian-Chat model can be used to power chatbots, virtual assistants, and other conversational AI applications targeting Russian or English users. Its capabilities make it well-suited for customer service, task automation, and creative writing applications. The model's flexibility and multilingual support also allow it to be integrated into applications serving diverse user bases.

Things to try

Try interacting with the model using the SambaLingo-chat-space demo on Hugging Face. You can experiment with different conversational prompts in Russian or English to see the model's response capabilities. Additionally, consider integrating the model into your own projects and applications to leverage its strong conversational abilities.



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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