nous-hermes-2-solar-10.7b-gguf
Maintainer: kcaverly
27
| 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
nous-hermes-2-solar-10.7b-gguf is the flagship Nous Research model built on the SOLAR 10.7B base model. It was developed by kcaverly, as described on their creator profile. This model is an improvement over the base SOLAR 10.7B, coming close to the performance of the Nous Hermes 2 - Yi-34B model. It was fine-tuned on over 1,000,000 entries of primarily GPT-4 generated data, as well as other high quality data from open datasets.
Similar models include the Nous Hermes 2 - SOLAR 10.7B and Nous-Hermes 2 - SOLAR 10.7B models, which share the same base architecture and training data. The Hermes-2 Θ (Theta) - Llama 8B is an earlier experimental model from Nous Research.
Model inputs and outputs
nous-hermes-2-solar-10.7b-gguf is a large language model that can take in free-form text prompts and generate coherent, context-appropriate responses. The model supports a variety of input formats, including the ChatML format used by OpenAI's ChatGPT.
Inputs
- Prompt: The text prompt provided to the model, which can include instructions, questions, or open-ended requests.
- Temperature: A parameter that controls the "warmth" or creativity of the model's responses, with higher values leading to more diverse and unexpected outputs.
- System Prompt: An optional system-level prompt that can help guide the model's behavior and persona.
- Max New Tokens: The maximum number of new tokens the model should generate in response.
- Repeat Penalty: A parameter that discourages the model from repeating itself too often, encouraging more diverse and dynamic responses.
- Prompt Template: An optional template for structuring the input prompt, which can be useful for multi-turn interactions.
Outputs
- Generated Text: The model's response, which can range from a single sentence to multiple paragraphs, depending on the input and parameters.
Capabilities
nous-hermes-2-solar-10.7b-gguf has demonstrated strong performance across a variety of benchmarks, including GPT4All, AGIEval, BigBench, and TruthfulQA. It has shown improvements over the base SOLAR 10.7B model in areas like reasoning, logical deduction, and truthfulness. The model is capable of engaging in open-ended conversations, answering questions, and providing detailed, coherent responses to prompts.
What can I use it for?
With its broad capabilities, nous-hermes-2-solar-10.7b-gguf can be used for a wide range of applications, from customer service chatbots to creative writing assistants. The model's ability to understand and follow complex instructions makes it well-suited for tasks like code generation, technical writing, and task planning. Its strong performance on benchmarks like TruthfulQA also suggests it could be useful for building trustworthy AI assistants.
Things to try
One interesting aspect of nous-hermes-2-solar-10.7b-gguf is its use of the ChatML prompt format, which allows for more structured and interactive conversations. Experimenting with different system prompts and prompt templates can help unlock the model's potential for engaging, multi-turn dialogues. Additionally, fine-tuning the model on domain-specific data could further enhance its capabilities for specialized tasks.
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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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 nous-hermes-2-yi-34b-gguf, 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.
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The Nous-Hermes-2-SOLAR-10.7B is the flagship Nous Research model on the SOLAR 10.7B base model. It was trained on 1,000,000 entries of primarily GPT-4 generated data, as well as other high quality data from open datasets across the AI landscape. This model is a significant improvement over the base SOLAR 10.7B model and approaches the performance of the Nous-Hermes-2-Yi-34B model across a variety of benchmarks. Model inputs and outputs The Nous-Hermes-2-SOLAR-10.7B model uses the ChatML prompt format, which allows for more structured multi-turn dialogue with the AI. This format enables OpenAI endpoint compatibility, and people familiar with the ChatGPT API will find the format familiar. Inputs Prompts following the ChatML format, with special tokens denoting the start and end of turns, as well as the roles of the participants. Outputs Coherent, contextually appropriate responses generated by the model based on the provided prompts. Capabilities The Nous-Hermes-2-SOLAR-10.7B model has demonstrated strong performance across a variety of benchmarks, including GPT4All, AGIEval, BigBench, and TruthfulQA. It excels at tasks like question answering, logical reasoning, and following complex instructions. What can I use it for? The Nous-Hermes-2-SOLAR-10.7B model can be used for a wide range of language tasks, from generating creative text to understanding and following complex instructions. It could be particularly useful for building conversational AI applications, like chatbots or virtual assistants, that require more structured and contextual interactions. Things to try One interesting aspect of the Nous-Hermes-2-SOLAR-10.7B model is its use of the ChatML prompt format. This allows for more sophisticated multi-turn dialogues, where the model can maintain context and coherence across multiple exchanges. Developers could experiment with building applications that leverage this capability, such as task-oriented chatbots or interactive writing assistants.
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