llama-3-youko-8b
Maintainer: rinna
55
🎲
| 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 |
Create account to get full access
Model overview
Llama 3 Youko 8B (rinna/llama-3-youko-8b) is a large language model developed by rinna. It is based on the Meta-Llama-3-8B model and has been continually pre-trained on a mixture of Japanese and English datasets, comprising around 22B tokens. This continual pre-training significantly improves the model's performance on Japanese tasks compared to the base Meta-Llama-3-8B model. The name "Youko" comes from the Japanese word for a mythical creature.
Model inputs and outputs
Llama 3 Youko 8B is a transformer-based language model that can be used for a variety of text-to-text tasks. It takes text as input and generates relevant output text.
Inputs
- Text prompts for language generation
Outputs
- Coherent, fluent text continuations based on the input prompts
- Responses to open-ended questions or instructions
- Translations between Japanese and English
Capabilities
The continual pre-training on Japanese and English datasets has endowed Llama 3 Youko 8B with strong language understanding and generation capabilities in both Japanese and English. It can engage in open-ended dialogue, summarize text, answer questions, and perform translation tasks between the two languages.
What can I use it for?
Llama 3 Youko 8B can be used for a variety of applications that require natural language processing, such as language learning, content generation, and multilingual communication. For example, it could be used to build chatbots or virtual assistants that can converse fluently in both Japanese and English, or to generate text for marketing, creative writing, or educational materials.
Things to try
One interesting aspect of Llama 3 Youko 8B is its ability to seamlessly switch between Japanese and English, allowing for bilingual applications and experiences. Developers could experiment with prompts that mix the two languages, or try fine-tuning the model on specialized Japanese or English datasets to further enhance its capabilities in those domains.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
Related Models
🎲
llama-3-youko-8b
55
Llama 3 Youko 8B (rinna/llama-3-youko-8b) is a large language model developed by rinna. It is based on the Meta-Llama-3-8B model and has been continually pre-trained on a mixture of Japanese and English datasets, comprising around 22B tokens. This continual pre-training significantly improves the model's performance on Japanese tasks compared to the base Meta-Llama-3-8B model. The name "Youko" comes from the Japanese word for a mythical creature. Model inputs and outputs Llama 3 Youko 8B is a transformer-based language model that can be used for a variety of text-to-text tasks. It takes text as input and generates relevant output text. Inputs Text prompts for language generation Outputs Coherent, fluent text continuations based on the input prompts Responses to open-ended questions or instructions Translations between Japanese and English Capabilities The continual pre-training on Japanese and English datasets has endowed Llama 3 Youko 8B with strong language understanding and generation capabilities in both Japanese and English. It can engage in open-ended dialogue, summarize text, answer questions, and perform translation tasks between the two languages. What can I use it for? Llama 3 Youko 8B can be used for a variety of applications that require natural language processing, such as language learning, content generation, and multilingual communication. For example, it could be used to build chatbots or virtual assistants that can converse fluently in both Japanese and English, or to generate text for marketing, creative writing, or educational materials. Things to try One interesting aspect of Llama 3 Youko 8B is its ability to seamlessly switch between Japanese and English, allowing for bilingual applications and experiences. Developers could experiment with prompts that mix the two languages, or try fine-tuning the model on specialized Japanese or English datasets to further enhance its capabilities in those domains.
Updated Invalid Date
🚀
Ko-Llama3-Luxia-8B
63
The Ko-Llama3-Luxia-8B is a large language model developed by Saltlux AI Labs. It is based on the Meta Llama-3 model, a collection of pretrained and instruction-tuned generative text models in 8 and 70 billion parameter sizes. The Llama-3 instruction-tuned models are optimized for dialogue use cases and outperform many available open-source chat models on common industry benchmarks. Model inputs and outputs The Ko-Llama3-Luxia-8B model takes in natural language text as input and generates coherent, context-appropriate responses. It can be used for a variety of text generation tasks, such as conversational AI, content creation, and question-answering. Inputs Natural language text prompts Outputs Generated text responses Capabilities The Ko-Llama3-Luxia-8B model is capable of engaging in open-ended dialogue, answering questions, and generating creative content. It has been trained on a large corpus of data, allowing it to draw upon a broad knowledge base to produce relevant and informative responses. What can I use it for? The Ko-Llama3-Luxia-8B model can be used for a wide range of applications, such as building conversational AI assistants, generating marketing copy or articles, and providing answers to user queries. Its versatility makes it a valuable tool for businesses and developers looking to incorporate advanced language AI into their products and services. Things to try One interesting aspect of the Ko-Llama3-Luxia-8B model is its ability to adapt to different conversational styles and tones. Users can experiment with providing the model with prompts in various formats, such as formal or informal language, to see how it responds and adjusts its output accordingly.
Updated Invalid Date
🤯
Llama-3-ELYZA-JP-8B
60
Llama-3-ELYZA-JP-8B is a large language model developed by ELYZA, Inc that has been enhanced for Japanese usage. It is based on the meta-llama/Meta-Llama-3-8B-Instruct model, but has undergone additional pre-training and instruction tuning to improve its performance on Japanese tasks. The model was developed by a team of researchers and engineers, including Masato Hirakawa, Shintaro Horie, Tomoaki Nakamura, Daisuke Oba, Sam Passaglia, and Akira Sasaki. Model inputs and outputs Inputs Text**: The model takes in text input, which can be used for tasks such as language generation, translation, and summarization. Outputs Text**: The model generates text output, which can be used for a variety of natural language processing tasks. Capabilities The Llama-3-ELYZA-JP-8B model has been trained to perform well on a variety of Japanese language tasks, including dialogue, question answering, and code generation. The model's enhanced performance on Japanese tasks makes it a useful tool for developers and researchers working with Japanese language data. What can I use it for? The Llama-3-ELYZA-JP-8B model can be used for a variety of natural language processing tasks in the Japanese language, such as: Language generation**: The model can be used to generate human-like text in Japanese, which can be useful for applications like chatbots, content creation, and language learning. Translation**: The model can be used to translate text between Japanese and other languages, which can be useful for international communication and collaboration. Question answering**: The model can be used to answer questions in Japanese, which can be useful for building knowledge-based applications and virtual assistants. Things to try One interesting thing to try with the Llama-3-ELYZA-JP-8B model is to use it for code generation in Japanese. The model's ability to understand and generate Japanese text can make it a useful tool for developers working on Japanese-language software projects. You can also try fine-tuning the model on specific Japanese language tasks or datasets to further improve its performance.
Updated Invalid Date
🗣️
Meta-Llama-3-8B
76
The Meta-Llama-3-8B is part of the Meta Llama 3 family of large language models (LLMs) developed and released by Meta. This collection of pretrained and instruction tuned generative text models comes in 8B and 70B parameter sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many available open source chat models on common industry benchmarks. Meta took great care to optimize helpfulness and safety when developing these models. The Meta-Llama-3-70B and Meta-Llama-3-8B-Instruct are other models in the Llama 3 family. The 70B parameter model provides higher performance than the 8B, while the 8B Instruct model is optimized for assistant-like chat. Model inputs and outputs Inputs The Meta-Llama-3-8B model takes text input only. Outputs The model generates text and code output. Capabilities The Meta-Llama-3-8B demonstrates strong performance on a variety of natural language processing benchmarks, including general knowledge, reading comprehension, and task-oriented dialogue. It excels at following instructions and engaging in open-ended conversations. What can I use it for? The Meta-Llama-3-8B is intended for commercial and research use in English. The instruction tuned version is well-suited for building assistant-like chat applications, while the pretrained model can be adapted for a range of natural language generation tasks. Developers can leverage the Llama Guard and other Purple Llama tools to enhance the safety and reliability of applications using this model. Things to try The clear strength of the Meta-Llama-3-8B model is its ability to engage in open-ended, task-oriented dialogue. Developers can leverage this by building conversational interfaces that leverage the model's instruction-following capabilities to complete a wide variety of tasks. Additionally, the model's strong grounding in general knowledge makes it well-suited for building information lookup tools and knowledge bases.
Updated Invalid Date