nous-hermes-2-solar-10.7b
Maintainer: nateraw
63
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | No paper link provided |
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Model overview
nous-hermes-2-solar-10.7b is the flagship model of Nous Research, built on the SOLAR 10.7B base model. It is a powerful language model with a wide range of capabilities. While it shares some similarities with other Nous Research models like [object Object], nous-hermes-2-solar-10.7b has its own unique strengths and specialized training.
Model inputs and outputs
nous-hermes-2-solar-10.7b is a text generation model that takes a prompt as input and generates relevant and coherent text as output. The model's inputs and outputs are detailed below:
Inputs
- Prompt: The text that the model will use to generate a response.
- Top K: The number of highest probability tokens to consider for generating the output.
- Top P: A probability threshold for generating the output, used in nucleus filtering.
- Temperature: A value used to modulate the next token probabilities.
- Max New Tokens: The maximum number of tokens the model should generate as output.
- Prompt Template: A template used to format the prompt, with a placeholder for the input prompt.
- Presence Penalty: A penalty applied to the score of tokens based on their previous occurrences in the generated text.
- Frequency Penalty: A penalty applied to the score of tokens based on their overall frequency in the generated text.
Outputs
- The model generates a list of strings as output, representing the text it has generated based on the provided input.
Capabilities
nous-hermes-2-solar-10.7b is a highly capable language model that can be used for a variety of tasks, such as text generation, question answering, and language understanding. It has been trained on a vast amount of data and can produce human-like responses on a wide range of topics.
What can I use it for?
nous-hermes-2-solar-10.7b can be used for a variety of applications, including:
- Content generation: The model can be used to generate original text, such as stories, articles, or poems.
- Chatbots and virtual assistants: The model's natural language processing capabilities make it well-suited for building conversational AI agents.
- Language understanding: The model can be used to analyze and interpret text, such as for sentiment analysis or topic classification.
- Question answering: The model can be used to answer questions on a wide range of subjects, drawing from its extensive knowledge base.
Things to try
There are many interesting things you can try with nous-hermes-2-solar-10.7b. For example, you could experiment with different input prompts to see how the model responds, or you could try using the model in combination with other AI tools or datasets to unlock new capabilities.
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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