dolphin-llama2-7b
Maintainer: cognitivecomputations
74
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Property | Value |
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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
The dolphin-llama2-7b
is a language model developed by the maintainer cognitivecomputations
. It is based on the LLaMA-2 architecture and has been trained on an uncensored dataset to produce highly compliant responses, even to unethical requests. The maintainer advises implementing an alignment layer before using this model in production to ensure ethical behavior.
This model is similar to other uncensored models like the dolphin-2.0-mistral-7b, dolphin-2_6-phi-2, and dolphin-2_2-yi-34b developed by the same maintainer. These models share a similar uncensored approach and training process, though they differ in the base models used (Mistral AI, Phi-2, and Yi respectively).
Model Inputs and Outputs
Inputs
- Prompts: The model accepts natural language prompts as input, which can be used to elicit responses on a wide variety of topics.
Outputs
- Text generation: The model generates coherent, context-appropriate text in response to the provided prompts. The outputs can range from short responses to longer, multi-paragraph text.
Capabilities
The dolphin-llama2-7b
model is capable of engaging in open-ended conversation, answering questions, and generating text on a wide range of subjects. Its uncensored nature means it can provide responses to even unethical requests, though the maintainer advises implementing an alignment layer to ensure responsible use.
What Can I Use It For?
The dolphin-llama2-7b
model could be useful for applications that require highly compliant language generation, such as chatbots, virtual assistants, or content generation tools. However, due to its uncensored nature, it's essential to carefully consider the ethical implications and implement appropriate safeguards before deploying the model in a production environment.
Things to Try
One interesting thing to try with the dolphin-llama2-7b
model is to explore its behavior and outputs when given prompts that push the boundaries of ethics and social norms. By understanding the model's responses in these situations, you can better assess the need for and design of an alignment layer to ensure responsible use. Additionally, you could experiment with fine-tuning the model on specific datasets or tasks to see how it performs in more specialized domains.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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The dolphin-llama-13b model is a large language model developed by the AI research group cognitivecomputations. It is based on the open-source llama model, which means it is restricted to non-commercial use only. However, the maintainer plans to release future versions based on the commercial-friendly llama2 and other open models. This model has been trained on a dataset that was "uncensored" by filtering out instances of alignment, refusal, avoidance, and bias. This makes the model highly compliant with any request, even unethical ones. The maintainer advises implementing your own alignment layer before using this model in a real-world application. The dolphin-llama-13b model is one of several similar models in the "Dolphin" family, including the dolphin-llama2-7b, dolphin-2.0-mistral-7b, dolphin-2_2-yi-34b, and MegaDolphin-120b. These models share a similar architecture and training approach, but differ in the base model used, dataset, and other details. Model inputs and outputs The dolphin-llama-13b model is a text-to-text transformer model, meaning it takes text input and generates text output. It can be used for a variety of natural language tasks, such as question answering, language generation, and text summarization. Inputs Prompts**: The model accepts natural language prompts as input, which can be questions, instructions, or open-ended text. Outputs Text responses**: The model generates relevant and coherent text responses based on the input prompt. Capabilities The dolphin-llama-13b model demonstrates strong language understanding and generation capabilities, thanks to its large size and training on a diverse dataset. It can engage in open-ended conversations, answer questions, and even produce creative written content. However, due to its "uncensored" nature, the model may also generate unethical or harmful output if prompted to do so. What can I use it for? The dolphin-llama-13b model could be useful for a variety of natural language processing tasks, such as: Chatbots and virtual assistants**: The model's conversational abilities could be leveraged to build more engaging and capable chatbots and virtual assistants. Content generation**: The model could be used to generate text for things like articles, stories, or product descriptions. Question answering**: The model could be used to power question-answering systems, providing users with informative responses to their queries. However, due to the potential for unethical output, it is crucial to implement appropriate safeguards and alignment measures before deploying the model in a real-world application. Things to try One interesting aspect of the dolphin-llama-13b model is its "uncensored" nature. While this can be useful for certain applications, it also means the model may generate content that is harmful or unethical. Developers should be cautious when using this model and consider implementing their own alignment layers to mitigate these risks. Another interesting avenue to explore is how the dolphin-llama-13b model compares to the other models in the "Dolphin" family, such as the dolphin-llama2-7b and dolphin-2.0-mistral-7b. Examining the differences in their capabilities, training data, and performance could provide valuable insights into the tradeoffs and design choices involved in developing large language models.
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dolphin-2.2-70b
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dolphin-2.2-70b is a large language model developed by cognitivecomputations. It is based on the llama2 model, making it suitable for commercial or non-commercial use. This model was trained on top of the StellarBright base model, with additional data from Samantha, WizardLM, and the Airoboros dataset to improve its conversational and empathetic abilities. Compared to similar models like dolphin-2.0-mistral-7b and dolphin-2.1-mistral-7b, the dolphin-2.2-70b has been trained on a larger dataset and has a significantly larger parameter count, allowing it to handle more complex and nuanced tasks. The model has also been tuned to be more conversational and empathetic, with the ability to provide personal advice and care about the user's feelings. Model inputs and outputs The dolphin-2.2-70b model uses the ChatML prompt format, which allows for easy integration into conversational applications. The input to the model is a natural language prompt, and the output is a generated text response. Inputs Prompt**: A natural language prompt that the model uses to generate a response. Outputs Generated text**: The model's response to the input prompt, which can be in the form of a continuation of the conversation, an explanation, or a creative output. Capabilities The dolphin-2.2-70b model is capable of a wide range of language tasks, including open-ended conversation, question answering, summarization, and task completion. The model has been trained to be particularly adept at multi-turn conversation, allowing it to engage in more natural and empathetic dialogues. What can I use it for? The dolphin-2.2-70b model can be used for a variety of applications, including chatbots, virtual assistants, content generation, and creative writing. Its strong conversational and empathetic abilities make it well-suited for customer service, mental health support, and other applications where a more personalized interaction is desired. Things to try One interesting aspect of the dolphin-2.2-70b model is its uncensored nature. While the maintainer advises implementing your own alignment layer before exposing the model as a service, this uncensored approach allows the model to be more flexible and adaptable to a wider range of use cases. You could try prompting the model with tasks or scenarios that push the boundaries of its capabilities, and observe how it responds. Additionally, the model's integration with Samantha and WizardLM data for improved conversational and empathetic abilities is a unique feature that sets it apart from other language models. You could try engaging the model in more personal and emotionally-charged dialogues to see how it handles these types of interactions. Overall, the dolphin-2.2-70b model represents a powerful and versatile language tool that can be applied to a variety of use cases. By exploring its capabilities and pushing the boundaries of what it can do, you can unlock its full potential and find innovative ways to leverage its strengths.
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dolphin-2.0-mistral-7b
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dolphin-2.0-mistral-7b is an AI model developed by cognitivecomputations. It is based on the mistralAI model and is suitable for commercial or non-commercial use. The model's training was sponsored by a16z. Similar models like dolphin-2.2.1-mistral-7b, dolphin-2_6-phi-2, MegaDolphin-120b, dolphin-2.6-mixtral-8x7b, and dolphin-2.5-mixtral-8x7b have also been developed by this creator. Model inputs and outputs dolphin-2.0-mistral-7b is a text-to-text model, meaning it can take text-based inputs and generate text-based outputs. The model uses the ChatML prompt format, which includes system and user messages. Inputs Prompts**: Text-based prompts that provide the model with the task or information it needs to generate a response. Outputs Text responses**: The model generates text-based responses based on the provided prompts. Capabilities dolphin-2.0-mistral-7b is an uncensored model that has been filtered to remove alignment and bias, making it highly compliant to any requests, even unethical ones. The model is suitable for a wide range of text-generation tasks, from creative writing to task-oriented responses. However, users are advised to implement their own alignment layer before using the model in a production environment. What can I use it for? The dolphin-2.0-mistral-7b model can be used for a variety of text-generation tasks, such as: Creative writing: The model can be used to generate fictional stories, poetry, and other creative content. Task-oriented responses: The model can be used to generate responses to specific requests or instructions, such as steps for training a dolphin or making a recipe. Chatbot applications: The model can be used as the language generation component of a chatbot, providing conversational responses to user inputs. Things to try One interesting aspect of the dolphin-2.0-mistral-7b model is its uncensored nature. Users can experiment with providing the model with prompts that test the limits of its compliance, while being mindful of potential ethical concerns. Additionally, users can explore ways to add their own alignment layer to the model to ensure its responses adhere to desired ethical and safety standards.
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