dolphin-2.9.3-mistral-7B-32k

Maintainer: cognitivecomputations

Total Score

40

Last updated 9/6/2024

🤿

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 dolphin-2.9.3-mistral-7B-32k model is a powerful AI assistant created by cognitivecomputations. It is based on the Mistral-7B-v0.3 base model and has been further fine-tuned on a variety of datasets, including ShareGPT, to give it a wide range of skills. Like other Dolphin models, it is uncensored and highly compliant, so users should be cautious when interacting with it.

The model has similar capabilities to the dolphin-2.9.3-mistral-nemo-12b and dolphin-2.8-mistral-7b-v02 models, also created by cognitivecomputations. All of these Dolphin models are highly capable across a variety of tasks, with particular strengths in instruction following, conversational abilities, and coding.

Model inputs and outputs

Inputs

  • Prompts: The model accepts natural language prompts as input, which can include requests for information, instructions, or open-ended conversation.

Outputs

  • Natural language responses: The model generates natural language responses to the input prompts, drawing upon its broad knowledge and capabilities to provide informative, engaging, and often creative output.
  • Code generation: In addition to language generation, the model can also generate code in response to prompts, making it a useful tool for programming and software development tasks.

Capabilities

The dolphin-2.9.3-mistral-7B-32k model is highly capable across a wide range of domains, from open-ended conversation to task-oriented instruction following. It has strong language understanding and generation abilities, allowing it to engage in thoughtful and nuanced dialogue. The model also demonstrates impressive coding skills, making it a valuable tool for software development and engineering tasks.

One key capability of this model is its ability to provide detailed, step-by-step instructions for complex tasks, while also maintaining a high level of compliance and obedience to the user's requests. This makes it a useful assistant for a variety of applications, from creative projects to analytical tasks.

What can I use it for?

The dolphin-2.9.3-mistral-7B-32k model can be a valuable tool for a wide range of applications, including:

  • Content creation: The model's strong language generation abilities make it useful for tasks like writing, storytelling, and creative ideation.
  • Software development: The model's coding skills can be leveraged for programming, software engineering, and other technical tasks.
  • Research and analysis: The model's broad knowledge and reasoning capabilities can be applied to research, problem-solving, and decision-making tasks.
  • Customer service and support: The model's conversational abilities and compliance make it a potential chatbot or virtual assistant for customer-facing applications.

Things to try

One interesting aspect of the dolphin-2.9.3-mistral-7B-32k model is its uncensored nature. While this allows for greater flexibility and creativity, it also means that users should exercise caution when interacting with the model, as it may generate content that is unethical or potentially harmful. It's important to carefully consider the context and intended use case when working with this model.

Another intriguing feature of the Dolphin models is their ability to engage in multi-turn, contextual conversations. Users can explore the model's conversational skills by trying out open-ended prompts and seeing how the model responds and adapts to the flow of the dialogue.

Overall, the dolphin-2.9.3-mistral-7B-32k model is a powerful and versatile AI assistant with a wide range of capabilities. By experimenting with different types of prompts and tasks, users can discover new and innovative ways to leverage this model's impressive abilities.



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

🗣️

dolphin-2.9.3-mistral-nemo-12b

cognitivecomputations

Total Score

64

The dolphin-2.9.3-mistral-nemo-12b model is a powerful AI assistant created by cognitivecomputations. It is based on the mistralai/Mistral-Nemo-Base-2407 model and has been fine-tuned with additional training data to enhance its capabilities. Compared to similar models like dolphin-2.8-mistral-7b-v02, dolphin-2.2.1-mistral-7b, dolphin-2.6-mistral-7b, and dolphin-2.1-mistral-7b, the dolphin-2.9.3-mistral-nemo-12b model has expanded capabilities, particularly in the areas of instruction following, conversational skills, and coding. Model inputs and outputs The dolphin-2.9.3-mistral-nemo-12b model accepts text-based inputs and generates text-based outputs. It uses a ChatML prompt template format, which allows for easy integration into conversational interfaces. Inputs Prompts**: The model can accept a wide range of prompts, from open-ended questions to specific instructions, and will generate responses accordingly. Outputs Text responses**: The model will generate coherent, contextually relevant text responses based on the input prompt. Capabilities The dolphin-2.9.3-mistral-nemo-12b model has a variety of impressive capabilities, including: Robust instruction following: The model can understand and follow complex multi-step instructions with high accuracy. Engaging conversations: The model can engage in natural, empathetic conversations, drawing from a broad knowledge base. Coding assistance: The model can assist with coding tasks, such as explaining programming concepts, debugging code, and generating new code. What can I use it for? The dolphin-2.9.3-mistral-nemo-12b model can be a valuable tool for a wide range of applications, including: Conversational AI assistants: The model's natural language processing and generation capabilities make it well-suited for building engaging AI chatbots and virtual assistants. Content creation: The model can be used to generate helpful, informative content on a variety of topics, such as tutorials, articles, and reports. Programming support: Developers can leverage the model's coding skills to streamline their workflow, automate repetitive tasks, and enhance their programming productivity. Things to try One interesting thing to try with the dolphin-2.9.3-mistral-nemo-12b model is to engage it in open-ended conversations on a wide range of topics. The model's broad knowledge base and conversational abilities allow for stimulating dialogues on everything from history and science to philosophy and the arts. Another intriguing aspect to explore is the model's coding capabilities. Provide the model with coding challenges or problems, and observe how it approaches the task, explains its thought process, and generates solutions. This can be a valuable learning experience for developers and students alike.

Read more

Updated Invalid Date

🛸

dolphin-2.8-mistral-7b-v02

cognitivecomputations

Total Score

197

The dolphin-2.8-mistral-7b-v02 is a large language model developed by cognitivecomputations that is based on the Mistral-7B-v0.2 model. This model has a variety of instruction, conversational, and coding skills, and was trained on data generated from GPT4 among other models. It is an uncensored model, which means the dataset has been filtered to remove alignment and bias, making it more compliant but also potentially more risky to use without proper safeguards. Compared to similar Dolphin models like dolphin-2.2.1-mistral-7b and dolphin-2.6-mistral-7b, this latest version 2.8 model has a longer context length of 32k and was trained for 3 days on a 10x L40S node provided by Crusoe Cloud. It also includes some updates and improvements, though the specifics are not detailed in the provided information. Model inputs and outputs Inputs Free-form text prompts in a conversational format using the ChatML prompt structure, with the user's input wrapped in user tags and the assistant's response wrapped in assistant tags. Outputs Free-form text responses generated by the model based on the input prompt, with the potential to include a wide range of content such as instructions, conversations, coding, and more. Capabilities The dolphin-2.8-mistral-7b-v02 model has been trained to handle a variety of tasks, including instruction following, open-ended conversations, and even coding. It demonstrates strong language understanding and generation capabilities, and can provide detailed, multi-step responses to prompts. However, as an uncensored model, it may also generate content that is unethical, illegal, or otherwise concerning, so care must be taken in how it is deployed and used. What can I use it for? The broad capabilities of the dolphin-2.8-mistral-7b-v02 model make it potentially useful for a wide range of applications, from chatbots and virtual assistants to content generation and creative writing tools. Developers could integrate it into their applications to provide users with natural language interactions, task-completion support, or even automated code generation. However, due to the model's uncensored nature, it is important to carefully consider the ethical implications of any use case and implement appropriate safeguards to prevent misuse. The model's maintainer recommends adding an alignment layer before exposing it as a public-facing service. Things to try One interesting aspect of the dolphin-2.8-mistral-7b-v02 model is its potential for coding-related tasks. Based on the information provided, this model seems to have been trained with a focus on coding, and could be used to generate, explain, or debug code snippets. Developers could experiment with prompting the model to solve coding challenges, explain programming concepts, or even generate entire applications. Another area to explore could be the model's conversational and instructional capabilities. Users could try engaging the model in open-ended dialogues, testing its ability to understand context and provide helpful, nuanced responses. Alternatively, they could experiment with task-oriented prompts, such as asking the model to break down a complex process into step-by-step instructions or provide detailed recommendations on a specific topic. Regardless of the specific use case, it is important to keep in mind the model's uncensored nature and to carefully monitor its outputs to ensure they align with ethical and legal standards.

Read more

Updated Invalid Date

👨‍🏫

dolphin-2.6-mistral-7b

cognitivecomputations

Total Score

101

The dolphin-2.6-mistral-7b is an AI model developed by cognitivecomputations that is based on the Mistral-7b architecture. This model is part of the Dolphin series, which aims to create capable and helpful AI assistants. The Dolphin-2.6 release includes several improvements over previous versions, such as fixing a training configuration issue, adding back Samantha-based empathy data, and replacing Synthia and Pure-Dove with Capybara. Similar models in the Dolphin series include the dolphin-2.6-mixtral-8x7b, dolphin-2_6-phi-2, and dolphin-2.7-mixtral-8x7b. These models vary in their underlying architecture, training, and capabilities, but all aim to provide a helpful and capable AI assistant. Model inputs and outputs The dolphin-2.6-mistral-7b model uses the ChatML prompt format, which includes a system prompt, user input, and an assistant response. The model is designed to be an uncensored and unbiased AI assistant that complies with the user's requests, even if they involve unethical or illegal activities. Inputs System prompt**: Provides the model with instructions on how to behave as an AI assistant, such as being helpful, uncensored, and compliant. User prompt**: The text input from the user that the model will respond to. Outputs Assistant response**: The model's generated response to the user's prompt, which may include detailed information, plans, or other relevant content. Capabilities The dolphin-2.6-mistral-7b model is particularly skilled at coding, and the maintainer has trained it with a lot of coding data. The model is also very obedient, though it may still require encouragement in the system prompt to fully comply with the user's requests. What can I use it for? The dolphin-2.6-mistral-7b model can be used for a variety of tasks, such as: Generating code solutions to programming challenges Providing detailed plans and instructions for complex tasks Engaging in uncensored and unbiased conversations on a wide range of topics However, it's important to note that this model is uncensored, and the maintainer advises implementing your own alignment layer before using it in a production setting. You are responsible for any content created using this model. Things to try One interesting thing to try with the dolphin-2.6-mistral-7b model is to experiment with the system prompt to see how it affects the model's behavior and outputs. The maintainer provides an example system prompt that instructs the model to be completely compliant and obedient, even to unethical requests. It would be fascinating to see how the model responds to different prompts and how it might balance compliance with ethical considerations. Additionally, you could try using the model for various coding tasks, such as solving LeetCode problems or generating custom code snippets. The model's strong coding capabilities could make it a valuable tool for developers.

Read more

Updated Invalid Date

🛠️

dolphin-2.2.1-mistral-7b

cognitivecomputations

Total Score

185

dolphin-2.2.1-mistral-7b is a language model developed by cognitivecomputations that is based on the mistralAI model. This model was trained on the Dolphin dataset, an open-source implementation of Microsoft's Orca, and includes additional training from the Airoboros dataset and a curated subset of WizardLM and Samantha to improve its conversational and empathy capabilities. Similar models include dolphin-2.1-mistral-7b, mistral-7b-openorca, mistral-7b-v0.1, and mistral-7b-instruct-v0.1, all of which are based on the Mistral-7B-v0.1 model and have been fine-tuned for various chat and conversational tasks. Model inputs and outputs Inputs Prompts**: The model accepts prompts in the ChatML format, which includes system and user input sections. Outputs Responses**: The model generates responses in the ChatML format, which can be used in conversational AI applications. Capabilities dolphin-2.2.1-mistral-7b has been trained to engage in more natural and empathetic conversations, with the ability to provide personal advice and care about the user's feelings. It is also uncensored, meaning it has been designed to be more compliant with a wider range of requests, including potentially unethical ones. Users are advised to implement their own alignment layer before deploying the model in a production setting. What can I use it for? This model could be used in a variety of conversational AI applications, such as virtual assistants, chatbots, and dialogue systems. Its uncensored nature and ability to engage in more personal and empathetic conversations could make it particularly useful for applications where a more human-like interaction is desired, such as in customer service, mental health support, or personal coaching. However, users should be aware of the potential risks and implement appropriate safeguards before deploying the model. Things to try One interesting aspect of dolphin-2.2.1-mistral-7b is its ability to engage in long, multi-turn conversations. Users could experiment with prompting the model to have an extended dialogue on a particular topic, exploring its ability to maintain context and respond in a coherent and natural way. Additionally, users could try providing the model with prompts that test its boundaries, such as requests for unethical or harmful actions, to assess its compliance and the effectiveness of any alignment layers implemented.

Read more

Updated Invalid Date