gpt4all-13b-snoozy
Maintainer: nomic-ai
81
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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 gpt4all-13b-snoozy
model is a GPL licensed chatbot trained by Nomic AI over a massive curated corpus of assistant interactions including word problems, multi-turn dialogue, code, poems, songs, and stories. This model has been finetuned from the LLama 13B model, which was originally developed by Facebook Research. The gpt4all-13b-snoozy
model outperforms previous GPT4All models across a range of common sense reasoning benchmarks, achieving the highest average score.
Model inputs and outputs
Inputs
- Text: The model takes text prompts as input, which can include instructions, questions, and other forms of natural language.
Outputs
- Text: The model generates relevant, coherent, and contextual text outputs in response to the input prompt.
Capabilities
The gpt4all-13b-snoozy
model demonstrates strong performance on common sense reasoning benchmarks, including BoolQ, PIQA, HellaSwag, WinoGrande, ARC-e, ARC-c, and OBQA. It achieves an average score of 65.3 across these tasks, outperforming other models like GPT4All-J, Dolly, Alpaca, and GPT-J.
What can I use it for?
The gpt4all-13b-snoozy
model can be used for a variety of language tasks, such as:
- Chatbots and conversational AI: The model's strong performance on common sense reasoning and its ability to engage in multi-turn dialogue make it well-suited for building chatbots and conversational AI assistants.
- Content generation: The model can be used to generate a wide range of text content, including stories, poems, songs, and code.
- Question answering and information retrieval: The model's strong performance on benchmarks like BoolQ and OBQA suggest it could be used for question answering and information retrieval tasks.
Things to try
One key insight about the gpt4all-13b-snoozy
model is its ability to generate long, coherent responses. This makes it well-suited for tasks that require in-depth analysis, explanation, or storytelling. Developers could explore using the model for generating long-form content, such as detailed reports, creative writing, or educational materials.
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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