Llama3-8B-Chinese-Chat-GGUF
Maintainer: zhouzr
44
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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
Llama3-8B-Chinese-Chat is an instruction-tuned language model developed by zhouzr that is specifically fine-tuned for Chinese and English users. It is based on the Meta-Llama-3-8B-Instruct model and uses the ORPO fine-tuning algorithm to significantly improve Chinese performance compared to the base model.
Compared to the original Meta-Llama-3-8B-Instruct, the Llama3-8B-Chinese-Chat model reduces issues with "Chinese questions and English answers" and the mixing of Chinese and English in responses. It also exhibits enhanced capabilities in areas like roleplaying, function calling, and mathematics.
Similar models include the Llama3-70B-Chinese-Chat which is a larger, higher-performance version of the model. The Llama3-Chinese-8B-Instruct is another related Chinese language model. These models provide alternative options for users with different performance requirements or use cases.
Model Inputs and Outputs
Llama3-8B-Chinese-Chat is a text-to-text model that takes conversational messages as input and generates relevant responses. The model can handle a mix of Chinese and English in the input and produces outputs in the appropriate language.
Inputs
- Conversational messages: The model accepts a series of messages in a conversational format, with each message containing a "role" (e.g. "system", "user") and "content" (the text of the message).
Outputs
- Generated text response: The model generates a text response to the provided conversational messages, continuing the conversation in a natural and coherent manner.
Capabilities
The Llama3-8B-Chinese-Chat model excels at tasks that require understanding and generation of Chinese and English text, such as:
- Roleplaying: The model can roleplay as different characters, using appropriate language and writing style to respond to prompts.
- Function calling: The model can understand and execute instructions to call predefined functions, such as searching the internet or directly answering questions.
- Mathematics: The model demonstrates strong capabilities in solving math problems, including arithmetic, algebra, and more complex mathematical reasoning.
What Can I Use It For?
The Llama3-8B-Chinese-Chat model can be a valuable tool for a variety of applications that involve Chinese and English language processing, such as:
- Multilingual chatbots: The model can be integrated into chatbot systems to provide natural language interactions in both Chinese and English.
- Language learning applications: The model can be used to create interactive learning experiences for users studying Chinese or English.
- Content generation: The model can be used to generate Chinese and English text for various applications, such as creative writing, article summarization, or language translation.
Things to Try
One interesting aspect of the Llama3-8B-Chinese-Chat model is its ability to handle mixed Chinese and English input and generate coherent responses. You can try providing the model with prompts that contain a mix of the two languages and see how it responds.
Another thing to explore is the model's performance on more complex tasks, such as solving advanced math problems or engaging in extended roleplaying scenarios. The model's strong capabilities in these areas suggest that it could be a valuable tool for educational or creative applications.
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Llama3-70B-Chinese-Chat is one of the first instruction-tuned LLMs for Chinese & English users with various abilities such as roleplaying, tool-using, and math, built upon the Meta-Llama/Meta-Llama-3-70B-Instruct model. According to the results from C-Eval and CMMLU, the performance of Llama3-70B-Chinese-Chat in Chinese significantly exceeds that of ChatGPT and is comparable to GPT-4. The model was developed by Shenzhi Wang and Yaowei Zheng. It was fine-tuned on a dataset containing over 100K preference pairs, with a roughly equal ratio of Chinese and English data. Compared to the original Meta-Llama-3-70B-Instruct model, Llama3-70B-Chinese-Chat significantly reduces issues of "Chinese questions with English answers" and the mixing of Chinese and English in responses. It also greatly reduces the number of emojis in the answers, making the responses more formal. Model inputs and outputs Inputs Free-form text prompts in either Chinese or English Outputs Free-form text responses in either Chinese or English, depending on the input language Capabilities Llama3-70B-Chinese-Chat exhibits strong performance in areas such as roleplaying, tool-using, and math, as demonstrated by its high scores on benchmarks like C-Eval and CMMLU. It is able to understand and respond fluently in both Chinese and English, making it a versatile assistant for users comfortable in either language. What can I use it for? Llama3-70B-Chinese-Chat could be useful for a variety of applications that require a language model capable of understanding and generating high-quality Chinese and English text. Some potential use cases include: Chatbots and virtual assistants for Chinese and bilingual users Language learning and translation tools Content generation for Chinese and bilingual media and publications Multilingual research and analysis tasks Things to try One interesting aspect of Llama3-70B-Chinese-Chat is its ability to seamlessly switch between Chinese and English within a conversation. Try prompting the model with a mix of Chinese and English, and see how it responds. You can also experiment with different prompts and topics to test the model's diverse capabilities in areas like roleplaying, math, and coding.
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Llama3.1-8B-Chinese-Chat is an instruction-tuned language model developed by Shenzhi Wang that is fine-tuned for Chinese and English users. It is built upon the Meta-Llama-3.1-8B-Instruct model and exhibits significant enhancements in roleplay, function calling, and math capabilities compared to the base model. The model was fine-tuned using the ORPO algorithm [1] on a dataset containing over 100K preference pairs with an equal ratio of Chinese and English data. This approach helps reduce issues like "Chinese questions with English answers" and the mixing of Chinese and English in responses, making the model more suitable for Chinese and English users. [1] Hong, Jiwoo, Noah Lee, and James Thorne. "Reference-free Monolithic Preference Optimization with Odds Ratio." arXiv preprint arXiv:2403.07691 (2024). Model inputs and outputs Inputs Textual prompts**: The model accepts textual prompts in Chinese, English, or a mix of both, covering a wide range of topics and tasks. Outputs Textual responses**: The model generates coherent and contextually appropriate textual responses in Chinese, English, or a mix of both, depending on the input prompt. Capabilities Llama3.1-8B-Chinese-Chat excels at tasks such as: Roleplaying**: The model can seamlessly switch between different personas and respond in a way that reflects the specified character's voice and personality. Function calling**: The model can understand and execute specific commands or actions, such as searching the internet or directly answering questions. Math**: The model demonstrates strong capabilities in solving math-related problems and explaining mathematical concepts. What can I use it for? The Llama3.1-8B-Chinese-Chat model can be useful for a variety of applications, such as: Chatbots and virtual assistants**: The model can be integrated into chatbots and virtual assistants to provide fluent and contextual responses in Chinese and English. Content generation**: The model can be used to generate coherent and creative content, such as stories, poems, or articles, in both Chinese and English. Educational and learning applications**: The model's strong performance in math and its ability to explain concepts can make it useful for educational and learning applications. Things to try One interesting thing to try with Llama3.1-8B-Chinese-Chat is its roleplay capabilities. You can experiment by providing the model with different character prompts and see how it adapts its responses accordingly. Additionally, the model's function calling abilities allow you to integrate it with various tools and services, opening up possibilities for building interactive and task-oriented applications.
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The Unichat-llama3-Chinese-8B is a large language model developed by UnicomLLM that has been fine-tuned on Chinese text data. It is based on the Meta Llama 3 model and has 8 billion parameters. Compared to similar models like Llama2-Chinese-13b-Chat-4bit and Llama2-Chinese-13b-Chat, the Unichat-llama3-Chinese-8B model has been specifically tailored for Chinese language tasks and aims to reduce issues like "Chinese questions with English answers" and the mixing of Chinese and English in responses. Model inputs and outputs The Unichat-llama3-Chinese-8B model takes in natural language text as input and generates relevant, coherent text as output. It can be used for a variety of natural language processing tasks, such as language generation, question answering, and text summarization. Inputs Natural language text in Chinese Outputs Relevant, coherent text in Chinese generated in response to the input Capabilities The Unichat-llama3-Chinese-8B model is capable of generating fluent, contextually appropriate Chinese text across a wide range of topics. It can engage in natural conversations, answer questions, and assist with various language-related tasks. The model has been fine-tuned to better handle Chinese language usage compared to more general language models. What can I use it for? The Unichat-llama3-Chinese-8B model can be used for a variety of applications that require Chinese language understanding and generation, such as: Building chatbots and virtual assistants for Chinese-speaking users Generating Chinese content for websites, blogs, or social media Assisting with Chinese language translation and text summarization Answering questions and providing information in Chinese Engaging in open-ended conversations in Chinese Things to try One interesting aspect of the Unichat-llama3-Chinese-8B model is its ability to maintain a consistent and coherent conversational flow while using appropriate Chinese language constructs. You could try engaging the model in longer dialogues on various topics to see how it handles context and maintains the logical progression of the conversation. Another area to explore is the model's performance on domain-specific tasks, such as answering technical questions or generating content related to certain industries or subject areas. The model's fine-tuning on Chinese data may make it particularly well-suited for these types of applications.
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