Kunoichi-DPO-v2-7B

Maintainer: SanjiWatsuki

Total Score

65

Last updated 5/28/2024

🖼️

PropertyValue
Run this modelRun on HuggingFace
API specView on HuggingFace
Github linkNo Github link provided
Paper linkNo paper link provided

Create account to get full access

or

If you already have an account, we'll log you in

Model overview

The Kunoichi-DPO-v2-7B model is a powerful general-purpose AI model developed by SanjiWatsuki. It is an evolution of the previous Kunoichi-7B model, with improvements in intelligence and performance across various benchmarks.

The Kunoichi-DPO-v2-7B model achieves strong results on key benchmarks like MT Bench, EQ Bench, MMLU, and Logic Test, outperforming many other models in its size range, including GPT-4-Turbo, GPT-4, and Mixtral-8x7B-Instruct. It also performs well on other evaluations like AGIEval, GPT4All, TruthfulQA, and BigBench.

Model inputs and outputs

Inputs

  • Text inputs, typically in the form of plain natural language prompts

Outputs

  • Text outputs, in the form of generated responses to the provided prompts

Capabilities

The Kunoichi-DPO-v2-7B model is a highly capable general-purpose AI system. It can engage in a wide variety of tasks, including natural language processing, question answering, creative writing, and problem-solving. The model's strong performance on benchmarks like MT Bench, EQ Bench, and MMLU suggests it has strong language understanding and reasoning abilities.

What can I use it for?

The Kunoichi-DPO-v2-7B model can be used for a wide range of applications, from content generation and creative writing to task assistance and research support. Potential use cases include:

  • Helping with research and analysis by summarizing key points, generating literature reviews, and answering questions
  • Assisting with creative projects like story writing, poetry generation, and dialogue creation
  • Providing task assistance and answering queries on a variety of topics
  • Engaging in open-ended conversations and roleplay

Things to try

One interesting aspect of the Kunoichi-DPO-v2-7B model is its strong performance on the Logic Test benchmark, which suggests it has robust logical reasoning capabilities. Users could try prompting the model with logical puzzles or hypothetical scenarios to see how it responds.

Additionally, the model's high scores on benchmarks like EQ Bench and TruthfulQA indicate it may have strong emotional intelligence and a tendency towards truthful and ethical responses. Users could explore these aspects by engaging the model in discussions about sensitive topics or by asking it to provide advice or make judgments.

Verify all URLs provided in links are contained within this prompt, and that all writing is in a clear, non-repetitive natural style.



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

🚀

Kunoichi-7B

SanjiWatsuki

Total Score

73

Kunoichi-7B is a general-purpose AI model created by SanjiWatsuki that is capable of role-playing. According to the maintainer, Kunoichi-7B is an extremely strong model that has the advantages of their previous models but with increased intelligence. Kunoichi-7B scores well on benchmarks that correlate closely with ChatBot Arena Elo, outperforming models like GPT-4, GPT-4 Turbo, and Starling-7B. Some similar models include Senku-70B-Full from ShinojiResearch, Silicon-Maid-7B from SanjiWatsuki, and una-cybertron-7b-v2-bf16 from fblgit. Model inputs and outputs Inputs Prompts**: The model can accept a wide range of prompts for tasks like text generation, answering questions, and engaging in role-play conversations. Outputs Text**: The model generates relevant and coherent text in response to the provided prompts. Capabilities Kunoichi-7B is a highly capable general-purpose language model that can excel at a variety of tasks. It demonstrates strong performance on benchmarks like MT Bench, EQ Bench, MMLU, and Logic Test, outperforming models like GPT-4, GPT-4 Turbo, and Starling-7B. The model is particularly adept at role-playing, able to engage in natural and intelligent conversations. What can I use it for? Kunoichi-7B can be used for a wide range of applications that involve natural language processing, such as: Content generation**: Kunoichi-7B can be used to generate high-quality text for articles, stories, scripts, and other creative projects. Chatbots and virtual assistants**: The model's role-playing capabilities make it well-suited for building conversational AI assistants. Question answering and information retrieval**: Kunoichi-7B can be used to answer questions and provide information on a variety of topics. Language translation**: While not explicitly mentioned, the model's strong language understanding capabilities may enable it to perform translation tasks. Things to try One interesting aspect of Kunoichi-7B is its ability to maintain the strengths of the creator's previous models while gaining increased intelligence. This suggests the model may be adept at tasks that require both strong role-playing skills and higher-level reasoning and analysis. Experimenting with prompts that challenge the model's logical and problem-solving capabilities, while also engaging its creative and conversational skills, could yield fascinating results. Additionally, given the model's strong performance on benchmarks, it would be worth exploring how Kunoichi-7B compares to other state-of-the-art language models in various real-world applications. Comparing its outputs and capabilities across different domains could provide valuable insights into its strengths and limitations.

Read more

Updated Invalid Date

🏷️

Kunoichi-DPO-v2-7B-GGUF

brittlewis12

Total Score

47

The Kunoichi-DPO-v2-7B-GGUF is a large language model created by SanjiWatsuki and maintained by brittlewis12. It is a version of the Kunoichi-DPO-v2-7B model that has been converted to the GGUF format, a new file format for representing AI models. The model is similar to other 7B language models like the CausalLM-7B-GGUF and the Neural-chat-7B-v3-1-GGUF, which have also been converted to the GGUF format. These models generally perform well on a variety of benchmarks, with the Kunoichi-DPO-v2-7B achieving strong results on tasks like MT Bench, EQ Bench, MMLU, and Logic Test. Model inputs and outputs Inputs Text prompt**: The model takes a text prompt as input, which can be a single sentence, a paragraph, or a longer piece of text. Outputs Generated text**: The model outputs generated text that continues or expands on the input prompt. The generated text can be used for tasks like text completion, story generation, and chatbot responses. Capabilities The Kunoichi-DPO-v2-7B-GGUF model is a capable language model that can be used for a variety of natural language processing tasks. It has shown strong performance on benchmarks like MT Bench, EQ Bench, MMLU, and Logic Test, indicating that it can handle tasks like machine translation, emotional intelligence, and logical reasoning. What can I use it for? The Kunoichi-DPO-v2-7B-GGUF model can be used for a wide range of applications, including: Text generation**: The model can be used to generate coherent and contextually relevant text, making it useful for tasks like story writing, content creation, and chatbot responses. Language understanding**: The model's strong performance on benchmarks like MMLU and Logic Test suggests that it could be used for tasks that require a deep understanding of language, such as question answering, reading comprehension, and sentiment analysis. Multimodal applications**: The model's potential for integration with visual information, as mentioned in the CausalLM-7B-GGUF model description, could make it useful for applications that involve both text and images, such as image captioning or visual question answering. Things to try One interesting aspect of the Kunoichi-DPO-v2-7B-GGUF model is its potential for use in character-based applications. The model's strong performance on emotional intelligence benchmarks suggests that it could be used to create engaging and lifelike virtual characters or chatbots that can interact with users in a more naturalistic way. Additionally, the model's ability to handle longer sequences of text, as mentioned in the CausalLM-7B-GGUF description, could make it useful for tasks that require generating or understanding longer pieces of text, such as creative writing, summarization, or document understanding.

Read more

Updated Invalid Date

🌐

Senku-70B-Full

ShinojiResearch

Total Score

139

Senku-70B-Full is a large language model developed by ShinojiResearch, a team of AI researchers and engineers. This model is a fine-tuned version of the 152334H/miqu-1-70b-sf model, which was originally trained on a synthesized Wikipedia conversation dataset. The fine-tuning process utilized the Slimorca dataset and a custom LoRA adapter to achieve state-of-the-art performance on several benchmark tasks. Compared to similar models like neural-chat-7b-v3-3 and 7B, Senku-70B-Full boasts impressive capabilities across a range of domains, including text generation, question answering, and commonsense reasoning. Model inputs and outputs Inputs Raw text prompts that can be used to guide the model's generation, such as instructions, queries, or dialogue contexts. Outputs Fluent, coherent text continuations that align with the provided input prompt. Responses to questions or information requests. Logical inferences and explanations based on the input context. Capabilities The Senku-70B-Full model has demonstrated strong performance on a variety of benchmark tasks, including the EQ-Bench, GSM8k, and Hellaswag. It can engage in thoughtful, contextually-appropriate dialogue, offer insightful analysis and commentary, and tackle complex reasoning problems. The model's broad knowledge and language understanding make it suitable for use in a wide range of applications, from chatbots and virtual assistants to content generation and question-answering systems. What can I use it for? With its impressive capabilities, the Senku-70B-Full model can be leveraged for a variety of applications, such as: Building conversational AI assistants that can engage in natural, informative dialogue Generating high-quality written content, such as articles, stories, or scripts Powering question-answering systems that can provide accurate and detailed responses Enhancing search and recommendation engines with advanced language understanding Enabling more sophisticated and personalized interactions in customer service and support applications Things to try One interesting aspect of the Senku-70B-Full model is its ability to adapt to different prompt formats, such as the ChatML template used in the neural-chat-7b-v3-3 model. Experimenting with various prompt styles and structures can help you unlock the model's full potential and find the most effective way to leverage its capabilities for your specific use case. Additionally, you may want to explore the model's performance on different types of tasks, such as creative writing, code generation, or multi-turn dialogue, to better understand its strengths and limitations. Comparing its outputs and behavior to other large language models can also provide valuable insights.

Read more

Updated Invalid Date

💬

Silicon-Maid-7B

SanjiWatsuki

Total Score

90

Silicon-Maid-7B is a text-to-text AI model created by SanjiWatsuki. This model is similar to other large language models like LLaMA-7B, animefull-final-pruned, and AsianModel, which are also focused on text generation tasks. While the maintainer did not provide a description for this specific model, the similar models suggest it is likely capable of generating human-like text across a variety of domains. Model inputs and outputs The Silicon-Maid-7B model takes in text as input and generates new text as output. This allows the model to be used for tasks like language translation, text summarization, and creative writing. Inputs Text prompts for the model to continue or expand upon Outputs Generated text that continues or expands upon the input prompt Capabilities The Silicon-Maid-7B model is capable of generating human-like text across a variety of domains. It can be used for tasks like language translation, text summarization, and creative writing. The model has been trained on a large corpus of text data, allowing it to produce coherent and contextually relevant output. What can I use it for? The Silicon-Maid-7B model could be used for a variety of applications, such as helping with content creation for businesses or individuals, automating text-based tasks, or even experimenting with creative writing. However, as with any AI model, it's important to use it responsibly and be aware of its limitations. Things to try Some ideas for experimenting with the Silicon-Maid-7B model include using it to generate creative story ideas, summarize long articles or reports, or even translate text between languages. The model's capabilities are likely quite broad, so there may be many interesting ways to explore its potential.

Read more

Updated Invalid Date