Pygmalion-13B-SuperHOT-8K-GPTQ
Maintainer: TheBloke
69
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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-13B-SuperHOT-8K-GPTQ model is a merge of TehVenom's Pygmalion 13B and Kaio Ken's SuperHOT 8K, quantized to 4-bit using GPTQ-for-LLaMa. It offers up to 8K context size, which has been tested to work with ExLlama and text-generation-webui.
Similar models include the Wizard-Vicuna-13B-Uncensored-SuperHOT-8K-GPTQ, which combines Eric Hartford's Wizard Vicuna 13B Uncensored with Kaio Ken's SuperHOT 8K, and the Llama-2-13B-GPTQ and Llama-2-7B-GPTQ models, which are GPTQ versions of Meta's Llama 2 models.
Model inputs and outputs
Inputs
- The model accepts natural language text as input.
Outputs
- The model generates natural language text as output.
Capabilities
The Pygmalion-13B-SuperHOT-8K-GPTQ model is capable of engaging in open-ended conversations and generating coherent and contextual text. Its extended 8K context size allows it to maintain continuity and coherence over longer passages of text.
What can I use it for?
This model could be used for a variety of natural language processing tasks, such as:
- Open-ended chatbots and assistants: The model's capabilities make it well-suited for building conversational AI assistants that can engage in open-ended dialogue.
- Content generation: The model could be used to generate text for creative writing, storytelling, and other content creation purposes.
- Question answering and knowledge retrieval: With its large knowledge base, the model could be used to answer questions and retrieve information on a wide range of topics.
Things to try
One key aspect of this model is its ability to maintain coherence and context over longer passages of text due to the increased 8K context size. This could be particularly useful for applications that require a strong sense of narrative or conversational flow, such as interactive fiction, roleplaying, or virtual assistants.
Developers could explore ways to leverage this extended context to create more immersive and coherent experiences for users, such as by allowing the model to maintain character personalities, world-building details, and the progression of a storyline over longer interactions.
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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