neuralbeagle14-7b-gguf
Maintainer: kcaverly
12
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | View on Arxiv |
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Model overview
neuralbeagle14-7b-gguf is a 7B language model created by kcaverly, available on Replicate. It is part of a collection of models shared by the maintainer, including similar large language models like Dolphin 2.5 Mixtral 8x7B GGUF and Nous Hermes 2 YI 34B GGUF. These models aim to provide powerful and flexible language capabilities for a variety of tasks.
Model inputs and outputs
neuralbeagle14-7b-gguf is a large language model that can generate human-like text based on provided prompts. The model takes in a text prompt as input and generates new text as output. Some key input and output details:
Inputs
- Prompt: The initial text that the model uses to generate new content.
- Temperature: A parameter that controls the "creativity" of the model's output, with higher values leading to more diverse and unpredictable text.
- System Prompt: A prompt that helps guide the model's behavior and persona.
- Max New Tokens: The maximum number of new tokens (words/subwords) the model will generate.
- Repeat Penalty: A parameter that discourages the model from repeating itself too often, encouraging more varied output.
Outputs
- Generated Text: The model's response, which can be used for a variety of language tasks such as writing, summarization, or dialogue.
Capabilities
neuralbeagle14-7b-gguf is a capable language model that can engage in open-ended conversation, answer questions, summarize text, and generate original content on a wide range of topics. It demonstrates strong natural language understanding and generation abilities, allowing it to produce coherent and contextually-appropriate text.
What can I use it for?
neuralbeagle14-7b-gguf can be used for a variety of language-based applications, such as:
- Content Generation: Generating news articles, blog posts, product descriptions, or other forms of written content.
- Language Modeling: Providing a foundation for building chatbots, virtual assistants, and other conversational AI systems.
- Text Summarization: Condensing long-form text into concise summaries.
- Question Answering: Answering questions on a wide range of topics based on its extensive knowledge.
Things to try
Some interesting things to explore with neuralbeagle14-7b-gguf include:
- Experimenting with different temperature and repeat penalty settings to see how they affect the model's creativity and coherence.
- Providing the model with prompts that require it to engage in multi-turn dialogue, and observing how it maintains context and continuity in its responses.
- Giving the model prompts that involve logical reasoning or task-completion, and evaluating its ability to follow instructions and provide helpful solutions.
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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