mpt-30B-chat-GGML
Maintainer: TheBloke
74
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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
mpt-30B-chat-GGML is a large language model created by the AI researcher TheBloke. It is a 30 billion parameter model trained to be a helpful, respectful, and honest AI assistant. The model is available in a GGML format, which allows for efficient CPU and GPU inference using tools like llama.cpp, text-generation-webui, and LM Studio.
Some similar models created by TheBloke include the goliath-120b-GGUF, Llama-2-13B-Chat-fp16, and the Llama-2-70B-Chat-GGML. These models share a focus on large-scale language generation and safe, helpful AI assistants.
Model inputs and outputs
Inputs
- Text prompt: The model takes a text prompt as input, which it uses to generate a coherent and contextually relevant response.
Outputs
- Generated text: The model outputs a continuation of the input text, in the form of a natural language response. The response aims to be helpful, respectful, and avoid harmful or unethical content.
Capabilities
The mpt-30B-chat-GGML model is capable of engaging in open-ended conversations, answering questions, and generating text on a wide variety of topics. It has been trained to provide helpful and safe responses, while avoiding harmful, unethical, or biased content. The model can be used for chatbots, virtual assistants, and other text generation applications.
What can I use it for?
The mpt-30B-chat-GGML model can be used for a variety of applications, including:
- Chatbots and virtual assistants: The model can be integrated into chatbots and virtual assistants to provide helpful and engaging responses to user queries.
- Content generation: The model can be used to generate text for articles, stories, social media posts, and other creative applications.
- Question answering: The model can be used to answer questions on a wide range of topics, drawing from its broad knowledge base.
Things to try
One interesting thing to try with the mpt-30B-chat-GGML model is to provide it with prompts that require nuanced or contextual understanding. For example, you could ask the model to provide a thoughtful and balanced analysis of a complex political or social issue, or to write a short story that explores a particular theme or emotion. The model's ability to generate coherent and contextually relevant text can be a powerful tool for exploring the boundaries of language and cognition.
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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