SUS-Chat-34B

Maintainer: SUSTech

Total Score

117

Last updated 5/28/2024

🔍

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

Get summaries of the top AI models delivered straight to your inbox:

Model overview

SUS-Chat-34B is a 34B bilingual Chinese-English dialogue model co-released by the Southern University of Science and Technology and IDEA-CCNL. This model is based on [object Object] and has been fine-tuned on millions of Chinese and English conversational data to excel at open-ended dialogue. Compared to similar models like Baichuan2-13B-Chat and yi-34b-chat, SUS-Chat-34B demonstrates state-of-the-art performance on benchmarks for open-ended dialogue in both languages.

Model inputs and outputs

Inputs

  • Conversational context: SUS-Chat-34B can accept multi-turn conversational history as input, allowing it to engage in coherent, contextual dialogues.
  • Text prompts: The model can also accept freeform text prompts on a wide range of topics, from creative writing to analytical tasks.

Outputs

  • Fluent, coherent text: The primary output of SUS-Chat-34B is human-like, contextually appropriate text responses to the given input.
  • Semantic understanding: Beyond just generating text, the model demonstrates strong language understanding capabilities, allowing it to follow instructions, answer questions, and engage in substantive discussions.

Capabilities

SUS-Chat-34B excels at open-ended conversational tasks, showcasing strong language understanding and generation abilities in both Chinese and English. It can engage in multi-turn dialogues, answer follow-up questions, and maintain coherence over long exchanges. The model also demonstrates competence in tasks like summarization, analysis, and creative writing.

What can I use it for?

The SUS-Chat-34B model can be leveraged for a variety of applications, such as:

  • Chatbots and virtual assistants: The model's dialogue capabilities make it well-suited for powering conversational interfaces in customer service, personal assistance, and other interactive applications.
  • Content generation: SUS-Chat-34B can be used to generate high-quality text content for blog posts, articles, marketing materials, and other use cases.
  • Language learning and education: The model's bilingual proficiency could be employed to create language learning tools and educational applications.

Things to try

One interesting aspect of SUS-Chat-34B is its ability to seamlessly switch between Chinese and English within a conversation, making it well-suited for multilingual applications. You could try prompting the model with a mix of Chinese and English inputs to see how it handles code-switching and maintains context across languages.

Another interesting direction to explore is the model's performance on specialized tasks, such as technical writing, legal analysis, or scientific summarization. By providing domain-specific prompts and evaluating the quality of the model's outputs, you can gain insights into its versatility and potential applications.



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

🔗

Baichuan2-13B-Chat

baichuan-inc

Total Score

398

Baichuan2-13B-Chat is a large language model developed by Baichuan Intelligence inc.. It is the 13 billion parameter version of the Baichuan 2 model series, which has achieved state-of-the-art performance on Chinese and English benchmarks of the same size. The Baichuan 2 series includes 7B and 13B versions for both Base and Chat models, as well as a 4-bit quantized version of the Chat model, allowing for efficient deployment across a variety of hardware. Similar models in the Baichuan line include the Baichuan-7B, a 7B parameter model that also performs well on Chinese and English benchmarks. Other comparable large language models include the Qwen-7B-Chat and the BELLE-7B-2M, both of which are 7B parameter models focused on language understanding and generation. Model Inputs and Outputs Baichuan2-13B-Chat is a text-to-text model, taking natural language prompts as input and generating coherent, contextual responses. The model has a context window length of 8,192 tokens, allowing it to maintain state over multi-turn conversations. Inputs Natural language prompts**: The model accepts free-form text prompts, which can range from simple questions to complex multi-sentence instructions. Outputs Generated text responses**: The model outputs generated text continuations that are relevant, coherent, and tailored to the input prompt. Responses can range from a single sentence to multiple paragraphs. Capabilities Baichuan2-13B-Chat has shown strong performance on a variety of language understanding and generation tasks, including question answering, open-ended conversation, and task completion. The model's large scale and specialized training allow it to engage in substantive, multi-turn dialogues while maintaining context and coherence. What Can I Use it For? Baichuan2-13B-Chat can be used for a wide range of natural language processing applications, such as: Virtual Assistants**: The model's conversational abilities make it well-suited for developing intelligent virtual assistants that can engage in open-ended dialogue. Content Generation**: Baichuan2-13B-Chat can be used to generate high-quality text for applications like creative writing, article summarization, and report generation. Question Answering**: The model's strong performance on benchmarks like MMLU and C-Eval indicate its suitability for building robust question-answering systems. To use Baichuan2-13B-Chat in your own projects, you can download the model from the Hugging Face Model Hub and integrate it using the provided code examples. For commercial use, you can obtain a license by emailing the maintainers. Things to Try One interesting aspect of Baichuan2-13B-Chat is its ability to handle multi-turn dialogues and maintain context over extended conversations. Try engaging the model in a back-and-forth discussion, providing relevant follow-up prompts and observing how it adapts its responses accordingly. Another area to explore is the model's performance on specialized tasks or domains. While the model has shown strong general capabilities, it may also excel at certain niche applications, such as technical writing, legal analysis, or domain-specific question answering. Experiment with prompts tailored to your specific use case and see how the model responds.

Read more

Updated Invalid Date

🖼️

Baichuan-13B-Chat

baichuan-inc

Total Score

632

Baichuan-13B-Chat is the aligned version in the Baichuan-13B series of models, with the pre-trained model available at Baichuan-13B-Base. Baichuan-13B is an open-source, commercially usable large-scale language model developed by Baichuan Intelligence, following Baichuan-7B. With 13 billion parameters, it achieves the best performance in standard Chinese and English benchmarks among models of its size. Model inputs and outputs The Baichuan-13B-Chat model is a text-to-text transformer that can be used for a variety of natural language processing tasks. It takes text as input and generates text as output. Inputs Text**: The model accepts text inputs that can be in Chinese, English, or a mix of both languages. Outputs Text**: The model generates text responses based on the input. The output can be in Chinese, English, or a mix of both languages. Capabilities The Baichuan-13B-Chat model has strong dialogue capabilities and is ready to use. It can be easily deployed with just a few lines of code. The model has been trained on a high-quality corpus of 1.4 trillion tokens, exceeding LLaMA-13B by 40%, making it the model with the most training data in the open-source 13B size range. What can I use it for? Developers can use the Baichuan-13B-Chat model for a wide range of natural language processing tasks, such as: Chatbots and virtual assistants**: The model's strong dialogue capabilities make it suitable for building chatbots and virtual assistants that can engage in natural conversations. Content generation**: The model can be used to generate various types of text content, such as articles, stories, or product descriptions. Question answering**: The model can be fine-tuned to answer questions on a wide range of topics. Language translation**: The model can be used for multilingual text translation tasks. Things to try The Baichuan-13B-Chat model has been optimized for efficient inference, with INT8 and INT4 quantized versions available that can be conveniently deployed on consumer GPUs like the Nvidia 3090 with almost no performance loss. Developers can experiment with these quantized versions to explore the trade-offs between model size, inference speed, and performance.

Read more

Updated Invalid Date

🔍

Baichuan2-7B-Chat

baichuan-inc

Total Score

149

Baichuan2-7B-Chat is a large language model released by Baichuan Intelligence Inc. It is a 7 billion parameter model trained on 2.6 trillion tokens, with versions for both base and chat tasks. The Baichuan2-13B-Chat model is a larger 13 billion parameter version also available. Compared to other models of similar size like Baichuan-7B, the Baichuan2 series has achieved state-of-the-art performance on Chinese and English benchmarks. Model inputs and outputs Inputs Text**: The Baichuan2-7B-Chat model can accept text inputs for generation tasks. Outputs Generated text**: The model can generate coherent and contextual text in response to the input. Capabilities The Baichuan2-7B-Chat model exhibits strong natural language understanding and generation capabilities across a variety of domains, from general knowledge to specialized areas like law, medicine, and mathematics. It outperforms similar-sized models like LLaMA and ChatGLM on Chinese and English benchmarks like C-Eval and MMLU. What can I use it for? The Baichuan2-7B-Chat model can be used for a wide range of text-based applications, such as: Content generation**: Generating articles, stories, or marketing copy Dialogue systems**: Building conversational chatbots and virtual assistants Question answering**: Providing informative responses to questions Code generation**: Assisting with programming tasks and code completion Additionally, developers can fine-tune the model for specific domains or tasks to further enhance its capabilities. The model is available for free academic research use, and commercial use is also possible after obtaining an official license from Baichuan Intelligence Inc. Things to try One interesting aspect of the Baichuan2-7B-Chat model is its ability to perform well on long-form text understanding and generation tasks, as demonstrated by its strong performance on the VCSUM dataset. This suggests the model may be particularly well-suited for applications involving summarization, analysis, or generation of lengthy, complex text.

Read more

Updated Invalid Date

🤖

Baichuan2-13B-Chat-4bits

baichuan-inc

Total Score

86

Baichuan2-13B-Chat-4bits is a version of the Baichuan 2 series of large language models developed by Baichuan Intelligence inc.. It is a 13B parameter model that has been quantized to 4 bits, allowing for faster inference speed and reduced memory usage compared to the full-precision version. Like the other Baichuan 2 models, it was trained on a high-quality corpus of 2.6 trillion tokens and has achieved strong performance on a variety of Chinese and English benchmarks. The Baichuan2-13B-Chat-4bits model shares many similarities with the Baichuan2-13B-Chat model, as they are both part of the Baichuan 2 series. The key difference is the quantization, which trades off some precision for improved efficiency. Compared to similar large language models of the same size, the Baichuan2 series models generally demonstrate stronger performance on Chinese and multilingual tasks. Model inputs and outputs Inputs Text prompts**: The model can accept text prompts of up to 4096 tokens as input. Outputs Generated text**: The model can generate coherent and contextually relevant text continuations in response to the input prompt. Capabilities The Baichuan2-13B-Chat-4bits model has strong language understanding and generation capabilities across a variety of domains, including general conversation, Q&A, task-completion, and more. It performs well on benchmarks covering areas like common sense reasoning, math problem-solving, and coding. The quantized version maintains much of this performance while improving efficiency. What can I use it for? The Baichuan2-13B-Chat-4bits model can be used for a wide range of NLP applications, such as: Chatbots and dialog systems**: The model can be fine-tuned to engage in natural conversations and assist with task completion. Content generation**: The model can be used to generate coherent and contextually relevant text, such as news articles, stories, or product descriptions. Question answering**: The model can be used to answer a variety of questions across different domains. Multilingual applications**: The model's strong performance on both Chinese and English makes it suitable for developing multilingual NLP applications. Developers can use the Baichuan2-13B-Chat-4bits model for free in commercial applications after obtaining an official commercial license through email request. Things to try One interesting aspect of the Baichuan2-13B-Chat-4bits model is its ability to handle long-form text generation and summarization tasks. The 4096 token context window and strong performance on the VCSUM benchmark suggest the model could be useful for applications like long-form content generation, document summarization, or even programming code generation and explanation. Another area to explore would be the model's multilingual capabilities. While the focus is on Chinese and English, the Baichuan2 series models have shown promising results on a variety of other languages as well. Developers could investigate using the model for multilingual applications or fine-tuning it on specialized datasets in other languages.

Read more

Updated Invalid Date