Pygmalion-2-13B-GPTQ
Maintainer: TheBloke
42
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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
The Pygmalion-2-13B-GPTQ is a quantized version of the Pygmalion 2 13B language model created by PygmalionAI. It is a merge of Pygmalion-2 13B and Gryphe's MythoMax 13B model. According to the maintainer TheBloke, this model seems to outperform the original MythoMax in roleplaying and chat tasks.
Similar quantized models available from TheBloke include the Mythalion-13B-GPTQ and the Llama-2-13B-GPTQ. These all provide different quantization options to optimize for performance on various hardware.
Model inputs and outputs
Inputs
- The model accepts text prompts as input, which can be formatted using the provided
<|system|>,<|user|>, and<|model|>tokens. This allows injecting context, indicating user input, and specifying where the model should generate a response.
Outputs
- The model generates text outputs in response to the provided prompts. It is designed to excel at roleplaying and creative writing tasks.
Capabilities
The Pygmalion-2-13B-GPTQ model is capable of generating coherent, contextual responses to prompts. It performs well on roleplaying and chat tasks, able to maintain a consistent persona and produce long-form responses. The model's capabilities make it suitable for applications like interactive fiction, creative writing assistants, and conversational AI agents.
What can I use it for?
The Pygmalion-2-13B-GPTQ model can be used for a variety of natural language generation tasks, with a particular focus on roleplaying and creative writing. Some potential use cases include:
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Interactive Fiction: The model's ability to maintain character personas and generate contextual responses makes it well-suited for developing choose-your-own-adventure style interactive fiction experiences.
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Creative Writing Assistance: The model can be used to assist human writers by generating text passages, suggesting plot ideas, or helping to develop characters and worlds.
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Conversational AI: The model's chat-oriented capabilities can be leveraged to build more natural and engaging conversational AI agents for customer service, virtual assistants, or other interactive applications.
Things to try
One interesting aspect of the Pygmalion-2-13B-GPTQ model is its use of the provided <|system|>, <|user|>, and <|model|> tokens to structure prompts and conversations. Experimenting with different ways to leverage this format, such as defining custom personas or modes for the model to operate in, can unlock novel use cases and interactions.
Additionally, trying out the various quantization options provided by TheBloke (e.g. 4-bit, 8-bit with different group sizes and Act Order settings) can help you find the best balance of performance and resource usage for your specific hardware and application requirements.
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
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Mythalion-13B-GPTQ
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The Mythalion-13B-GPTQ is a large language model created by PygmalionAI and quantized to 4-bit and 8-bit precision by TheBloke. It is based on the original Mythalion 13B model and provides multiple GPTQ parameter configurations to optimize for different hardware and inference requirements. Similar quantized models from TheBloke include the MythoMax-L2-13B-GPTQ and wizard-mega-13B-GPTQ. Model inputs and outputs The Mythalion-13B-GPTQ is a text-to-text model, taking in natural language prompts and generating relevant text responses. It was fine-tuned on various datasets to enhance its conversational and storytelling capabilities. Inputs Natural language prompts or instructions Outputs Generated text responses relevant to the input prompt Capabilities The Mythalion-13B-GPTQ model excels at natural language understanding and generation, allowing it to engage in open-ended conversations and produce coherent, contextually-appropriate text. It performs well on tasks like creative writing, dialogue systems, and question-answering. What can I use it for? The Mythalion-13B-GPTQ model can be used for a variety of natural language processing applications, such as building interactive chatbots, generating creative fiction and dialog, and enhancing language understanding in other AI systems. Its large scale and diverse training data make it a powerful tool for developers and researchers working on language-focused projects. Things to try Try giving the model prompts that involve storytelling, world-building, or roleplaying scenarios. Its strong understanding of context and ability to generate coherent, imaginative text can lead to engaging and surprising responses. You can also experiment with different quantization configurations to find the best balance between model size, inference speed, and accuracy for your specific use case.
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Llama-2-13B-GPTQ
118
The Llama-2-13B-GPTQ model is a quantized version of Meta's 13B-parameter Llama 2 large language model. It was created by TheBloke, who has made several optimized GPTQ and GGUF versions of the Llama 2 models available on Hugging Face. This model provides a balance between performance, size, and resource usage compared to other similar quantized Llama 2 models like the Llama-2-7B-GPTQ and Llama-2-70B-GPTQ. Model inputs and outputs Inputs Text**: The model takes text prompts as input, which it then uses to generate additional text. Outputs Text**: The model outputs generated text, which can be used for a variety of natural language tasks such as dialogue, summarization, and content creation. Capabilities The Llama-2-13B-GPTQ model is capable of engaging in open-ended dialogue, answering questions, and generating human-like text on a wide range of topics. It performs well on commonsense reasoning, world knowledge, and reading comprehension tasks. The model has also been fine-tuned for safety and helpfulness, making it suitable for use in assistant-like applications. What can I use it for? You can use the Llama-2-13B-GPTQ model for a variety of natural language processing tasks, such as: Chatbots and virtual assistants**: The model's dialogue capabilities make it well-suited for building conversational AI assistants. Content generation**: You can use the model to generate text for things like articles, stories, and social media posts. Question answering**: The model can be used to build systems that can answer questions on a wide range of subjects. Summarization**: The model can be used to summarize long passages of text. Things to try One interesting thing to try with the Llama-2-13B-GPTQ model is to experiment with different temperature and top-k/top-p sampling settings to see how they affect the model's output. Higher temperatures can lead to more diverse and creative text, while lower temperatures result in more coherent and focused output. Adjusting these settings can help you find the right balance for your specific use case. Another interesting experiment is to use the model in a few-shot or zero-shot learning setting, where you provide the model with just a few examples or no examples at all of the task you want it to perform. This can help you understand the model's few-shot and zero-shot capabilities, and how it can be adapted to new tasks with minimal additional training.
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Llama-2-13B-chat-GPTQ
357
The Llama-2-13B-chat-GPTQ model is a version of Meta's Llama 2 13B language model that has been quantized using GPTQ, a technique for reducing the model's memory footprint without significant loss in quality. This model was created by TheBloke, a prominent AI researcher and developer. TheBloke has also made available GPTQ versions of the Llama 2 7B and 70B models, as well as other quantized variants using different techniques. The Llama-2-13B-chat-GPTQ model is designed for chatbot and conversational AI applications, having been fine-tuned by Meta on dialogue data. It outperforms many open-source chat models on standard benchmarks and is on par with closed-source models like ChatGPT and PaLM in terms of helpfulness and safety. Model inputs and outputs Inputs The model accepts text input, which can be prompts, questions, or conversational messages. Outputs The model generates text output, which can be responses, answers, or continuations of the input. Capabilities The Llama-2-13B-chat-GPTQ model demonstrates strong natural language understanding and generation capabilities. It can engage in open-ended dialogue, answer questions, and assist with a variety of natural language tasks. The model has been imbued with an understanding of common sense and world knowledge, allowing it to provide informative and contextually relevant responses. What can I use it for? The Llama-2-13B-chat-GPTQ model is well-suited for building chatbots, virtual assistants, and other conversational AI applications. It can be used to power customer service bots, AI tutors, creative writing assistants, and more. The model's capabilities also make it useful for general-purpose language generation tasks, such as content creation, summarization, and language translation. Things to try One interesting aspect of the Llama-2-13B-chat-GPTQ model is its ability to maintain a consistent personality and tone across conversations. You can experiment with different prompts and see how the model adapts its responses to the context and your instructions. Additionally, you can try providing the model with specific constraints or guidelines to observe how it navigates ethical and safety considerations when generating text.
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MythoMax-L2-13B-GPTQ
161
Gryphe's MythoMax L2 13B is a large language model created by Gryphe and supported by a grant from andreessen horowitz (a16z). It is similar in size and capabilities to other prominent open-source models like the Llama 2 7B Chat and Falcon 180B Chat, but with a focus on mythological and fantastical content. Model inputs and outputs MythoMax-L2-13B-GPTQ is a text-to-text generative model, meaning it takes text prompts as input and generates new text as output. The model was trained on a large dataset of online text, with a focus on mythological and fantasy-related content. Inputs Text prompts**: The model takes freeform natural language text as input, which it then uses to generate new text in response. Outputs Generated text**: The model outputs new text that continues or expands upon the provided input prompt. The output can range from a single sentence to multiple paragraphs, depending on the prompt and the model's parameters. Capabilities The MythoMax-L2-13B-GPTQ model is capable of generating engaging, coherent text on a wide variety of fantasy and mythological topics. It can be used to produce creative stories, worldbuilding details, character dialogue, and more. The model's knowledge spans mythological creatures, legends, magical systems, and other fantastical concepts. What can I use it for? The MythoMax-L2-13B-GPTQ model is well-suited for all kinds of fantasy and science-fiction writing projects. Writers and worldbuilders can use it to generate ideas, expand on existing stories, or flesh out the details of imaginary realms. It could also be leveraged for interactive storytelling applications, roleplaying games, or even AI-generated fanfiction. Things to try Try prompting the model with the beginning of a fantastical story or worldbuilding prompt, and see how it continues the narrative. You can also experiment with more specific requests, like asking it to describe a particular mythological creature or magical ritual. The model's responses may surprise you with their creativity and attention to detail.
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