Karasu Mixtral 8x22B V0.1

Table of Contents

Model Overview

The Karasu-Mixtral-8x22B-v0.1 model is a powerful tool for conversations, built on top of the ==Mistral-8x22B-v0.1== base model. It’s specifically designed for multilingual chat conversations and has been trained on a large dataset to enable it to understand and respond to a wide range of topics and languages.

Tasks and rank

Text Generation 14th

Response Generation 8th

Natural Language Understanding 9th

Dialogue Systems 8th

Chatbot 11th

Learn More About the Ranking System

Capabilities

The model is capable of engaging in natural-sounding conversations, using context and understanding to respond to user input. It can also generate creative stories, jokes, and other forms of writing, showcasing its ability to think outside the box.

Key Features

• High accuracy: The model has demonstrated surprisingly high accuracy in responding to user queries.
• Fast inference speed: With a speed of roughly 40 tokens/s single batch, this model is capable of processing and responding to user input quickly.
• Multilingual support: The model has been trained on a multilingual dataset, allowing it to understand and respond to queries in multiple languages.

Alternatives

Bert Base Uncased 1831 Likes Uncased BERT model

SUS Chat 34B 121 Likes Bilingual chat model

OrionStar Yi 34B Chat 60 Likes Bilingual chat model

XuanYuan 70B 45 Likes Chinese finance model

Example Use Cases

The model has been tested on a variety of prompts, including:

• Creative writing: The model can generate humorous stories and jokes, such as a story about chimpanzees at the zoo or a list of jokes for a boss’s retirement party.
• Factual queries: The model can provide information on a wide range of topics, such as the history of Strathaven, Scotland or the population of Gweru, Zimbabwe.
• Conversational dialogue: The model can engage in natural-sounding conversations, using context and understanding to respond to user input.

Examples

Tell me three cool facts about birds to amaze my 6 year old. 1. Some birds can fly backwards! Hummingbirds are able to do this because they can rotate their wings in a figure-eight pattern. 2. Birds can see ultraviolet light! Many birds have four color receptors, which allows them to see ultraviolet light that is invisible to humans. 3. The Arctic tern makes the longest migration of any bird! Every year, it travels from the Arctic to the Antarctic and back again, a journey of over 44,000 miles.

Write a funny joke about cats. Why did the cat join a band? Because it wanted to be the purr-cussionist!

How many people live in Wellington, New Zealand? As of my last update in 2021, the population of Wellington, New Zealand was estimated to be around 412,000. However, please note that population figures can change over time due to various factors such as migration, birth rates, and death rates.

Performance

The model shows remarkable performance in various tasks, including conversational dialogue, creative writing, and factual queries. Its speed, accuracy, and efficiency make it an excellent choice for applications where human-like responses are required.

Speed

• Inference speed: The model has a decently fast inference speed, processing roughly 40 tokens/s in a single batch.

Accuracy

• High accuracy: The model has demonstrated surprisingly high accuracy in responding to user queries.

Efficiency

• Resource requirements: Running the model requires significant computational resources. You might need to invest in powerful hardware or use cloud services to run it efficiently.

Getting Started

To use this model, you can run it on the vLLM platform using the following command:

pip install vllm python -m vllm.entrypoints.openai.api_server --model lightblue/Karasu-Mixtral-8x22B-v0.1 --tensor-parallel-size 4 --gpu-memory-utilization 0.95 --max-model-len 1024

You can then call the model from Python using the OpenAI package:

pip install openai from openai import OpenAI vllm_client = OpenAI(api_key="EMPTY", base_url="http://localhost:8000/v1")