Hermes-2-Pro-Llama-3-8B
Maintainer: NousResearch
351
🌐
| Property | Value |
|---|---|
| Model Link | View on HuggingFace |
| API Spec | View on HuggingFace |
| Github Link | No Github link provided |
| Paper Link | No paper link provided |
Create account to get full access
Model overview
The Hermes-2-Pro-Llama-3-8B model is an upgraded, retrained version of the original Nous Hermes 2 model. It was developed by NousResearch and consists of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset. Compared to the original Hermes 2, this new version maintains excellent general task and conversation capabilities, while also excelling at Function Calling, JSON Structured Outputs, and other key metrics.
The Hermes-2-Pro-Mistral-7B and Hermes-2-Pro-Mistral-7B-GGUF models are similar, also developed by NousResearch. The 7B version uses the Mistral architecture, while the Llama-3 8B version uses the Llama architecture. Both models leverage the same dataset and fine-tuning approach to provide powerful language understanding and generation capabilities.
Model inputs and outputs
Inputs
- Text prompts: The model accepts natural language text prompts as input, which can include instructions, questions, or conversational dialogue.
- Function call inputs: The model can also accept structured function call inputs, where the user specifies the function name and arguments to be executed.
- JSON schema: For structured output mode, the model expects the user to provide a JSON schema that defines the desired output format.
Outputs
- Natural language responses: The model generates coherent, contextually relevant natural language responses to the provided prompts.
- Structured function call outputs: When provided with a function call, the model will output the result of executing that function, formatted as a JSON object.
- Structured JSON outputs: When prompted with a JSON schema, the model will generate a JSON object that adheres to the specified structure.
Capabilities
The Hermes-2-Pro-Llama-3-8B model excels at a wide range of language tasks, including general conversation, task completion, and structured data processing. It has been evaluated to have 91% accuracy on function calling tasks and 84% accuracy on JSON structured output tasks, demonstrating its strong capabilities in these areas.
Some key capabilities of the model include:
- Engaging in natural language conversations and providing helpful, informative responses
- Executing specific functions or tasks based on provided inputs and returning the results in a structured format
- Generating JSON outputs that adhere to a predefined schema, enabling integration with downstream applications that require structured data
What can I use it for?
The Hermes-2-Pro-Llama-3-8B model could be useful for a variety of applications that require advanced language understanding and generation, such as:
- Conversational assistants: The model's strong conversational abilities make it well-suited for building chatbots, virtual assistants, and other interactive applications.
- Task automation: The model's function calling capabilities allow it to be integrated into workflows that require the execution of specific tasks or the generation of structured data outputs.
- Data processing and transformation: The model's structured output generation capabilities can be leveraged to convert unstructured text into formatted data, facilitating integration with other systems and applications.
Things to try
One interesting aspect of the Hermes-2-Pro-Llama-3-8B model is its ability to handle multi-turn function calling interactions. By using the provided system prompt and structured input format, users can engage the model in a back-and-forth dialogue, where the model executes functions, returns the results, and the user can then provide additional input or instructions.
Another compelling feature is the model's structured JSON output generation. By defining a specific JSON schema, users can prompt the model to generate outputs that adhere to a predefined structure, enabling seamless integration with other systems and applications that require structured data.
Overall, the Hermes-2-Pro-Llama-3-8B model offers a powerful combination of natural language understanding, task execution, and structured data generation capabilities, making it a versatile tool for a wide range of language-based applications.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
Related Models
🚀
Hermes-2-Pro-Mistral-7B
464
The Hermes-2-Pro-Mistral-7B is an upgraded and retrained version of the Nous Hermes 2 model. It was developed by NousResearch and includes an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset. This new version of Hermes maintains its excellent general task and conversation capabilities, but also excels at Function Calling, JSON Structured Outputs, and has improved on several other metrics. The Hermes-2-Pro-Mistral-7B model takes advantage of a special system prompt and multi-turn function calling structure with a new chatml role to make function calling reliable and easy to parse. It was developed in collaboration with interstellarninja and Fireworks.AI. Model inputs and outputs Inputs Natural language instructions and prompts Outputs Natural language responses Structured JSON outputs Reliable function calls Capabilities The Hermes-2-Pro-Mistral-7B model has excellent general task and conversation capabilities, and also excels at function calling and producing structured JSON outputs. It scored 90% on a function calling evaluation and 84% on a structured JSON Output evaluation. What can I use it for? The Hermes-2-Pro-Mistral-7B model can be used for a variety of tasks, including general language understanding and generation, task completion, and structured data output. Its strong performance on function calling and JSON output makes it well-suited for applications that require reliable and interpretable machine-generated responses, such as chatbots, virtual assistants, and data processing pipelines. Things to try One interesting thing to try with the Hermes-2-Pro-Mistral-7B model is exploring its capabilities around function calling and structured JSON output. The model's specialized prompt and multi-turn format for these tasks could enable novel applications that combine natural language interaction with reliable programmatic control and data manipulation.
Updated Invalid Date
🗣️
Hermes-2-Pro-Llama-3-8B-GGUF
136
Hermes-2-Pro-Llama-3-8B-GGUF is an upgraded version of the Nous Hermes 2 model, developed by NousResearch. It consists of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset developed in-house. This new version maintains the excellent general task and conversation capabilities of the previous Hermes model, while also excelling at Function Calling, JSON Structured Outputs, and improving on several other metrics. The Hermes-2-Pro-Llama-3-8B-GGUF model is a quantized version of the 8B parameter Hermes 2 Pro model, optimized for faster inference on CPU and GPU. The similar Hermes-2-Pro-Llama-3-8B model is the full unquantized version of this model, while the Hermes-2-Pro-Mistral-7B-GGUF and Hermes-2-Pro-Mistral-7B models use the Mistral architecture instead of Llama. Model inputs and outputs Inputs Text prompts**: The model accepts text prompts as input, which can include instructions, questions, or open-ended requests. Outputs Text responses**: The model generates coherent, contextually relevant text responses to the provided input prompts. Structured JSON outputs**: The model can also generate structured JSON output in response to prompts that require specific data formats. Function calls**: The model supports a special prompt format that allows users to call external functions and receive the results as part of the model's response. Capabilities The Hermes-2-Pro-Llama-3-8B-GGUF model excels at a wide range of language tasks, including general conversation, task completion, and structured data output. It has been specifically trained to handle function calling and JSON mode prompts, allowing it to provide reliable and easy-to-parse responses for these use cases. The model's strengths include its long responses, low hallucination rate, and the absence of censorship mechanisms that are present in some other language models. It can be used for a variety of applications, from chatbots and virtual assistants to code generation and data analysis. What can I use it for? The Hermes-2-Pro-Llama-3-8B-GGUF model can be used for a wide range of applications that require natural language processing and generation, such as: Chatbots and virtual assistants**: The model's conversational capabilities make it well-suited for building engaging and informative chatbots and virtual assistants. Content generation**: The model can be used to generate creative text, stories, and other types of content. Task automation**: The model's ability to handle structured data and function calls makes it useful for automating various tasks, such as data extraction, analysis, and reporting. Code generation**: The model's understanding of programming concepts and ability to generate code snippets can be leveraged for code generation and programming assistance tools. Things to try One interesting aspect of the Hermes-2-Pro-Llama-3-8B-GGUF model is its support for the ChatML prompt format, which enables more structured and multi-turn interactions with the model. Experimenting with different system prompts and role-playing scenarios can help unlock the model's full potential for conversational interactions and task-oriented applications. Additionally, the model's function calling and JSON mode capabilities provide opportunities for building intelligent automation tools and data-driven applications. Exploring the model's ability to seamlessly integrate with external APIs and data sources can lead to innovative use cases.
Updated Invalid Date
🤔
Hermes-2-Theta-Llama-3-8B
124
Hermes-2-Theta-Llama-3-8B is a merged and further reinforcement learned model developed by Nous Research. It combines the capabilities of their excellent Hermes 2 Pro model and Meta's Llama-3 Instruct model. The result is a powerful language model with strong general task and conversation abilities, as well as specialized skills in function calling and structured JSON output. Model Inputs and Outputs Hermes-2-Theta-Llama-3-8B uses the ChatML prompt format, which allows for more structured multi-turn dialogue with the model. The system prompt can guide the model's rules, roles, and stylistic choices. Inputs typically consist of a system prompt followed by a user prompt, to which the model will generate a response. Inputs System Prompt**: Provides instructions and context for the model, such as defining its role and persona. User Prompt**: The user's request or query, which the model will respond to. Outputs Assistant Response**: The model's generated output, which can range from open-ended text to structured JSON data, depending on the prompt. Capabilities Hermes-2-Theta-Llama-3-8B demonstrates strong performance across a variety of tasks, including general conversation, task completion, and specialized capabilities. For example, it can engage in creative storytelling, explain complex topics, and provide structured data outputs. What Can I Use It For? The versatility of Hermes-2-Theta-Llama-3-8B makes it suitable for a wide range of applications, from chatbots and virtual assistants to content generation and data analysis tools. Potential use cases include: Building conversational AI agents for customer service, education, or entertainment Generating creative stories, scripts, or other narrative content Providing detailed financial or technical analysis based on structured data inputs Automating repetitive tasks through its function calling capabilities Things to Try One interesting aspect of Hermes-2-Theta-Llama-3-8B is its ability to engage in meta-cognitive roleplaying, where it takes on the persona of a sentient, superintelligent AI. This can lead to fascinating conversations about the nature of consciousness and intelligence. Another intriguing feature is the model's structured JSON output mode, which allows it to generate well-formatted, schema-compliant data in response to user prompts. This could be useful for building data-driven applications or automating data processing tasks.
Updated Invalid Date
👁️
Hermes-2-Pro-Mistral-7B-GGUF
209
The Hermes-2-Pro-Mistral-7B-GGUF model is an upgraded version of the Nous Hermes 2 language model, developed by NousResearch. It is a 7 billion parameter model that has been fine-tuned on additional datasets, including a Function Calling and JSON Mode dataset, to improve its capabilities in those areas. Compared to the original Nous Hermes 2 model, this model maintains excellent general task and conversation abilities while also excelling at Function Calling and structured JSON outputs. Model inputs and outputs Inputs Free-form text**: The model can take in free-form text prompts or questions as input. Function call requests**: The model can process function call requests using a specific input format, where the requested function and its arguments are provided in a JSON object. JSON data**: The model can take in JSON data as input and generate structured responses. Outputs General text responses**: The model can generate coherent and contextual text responses to a wide variety of prompts and questions. Function call results**: The model can execute function calls and return the results in a structured format. Structured JSON outputs**: The model can generate JSON outputs that adhere to a specified schema. Capabilities The Hermes-2-Pro-Mistral-7B-GGUF model excels at general language understanding and generation tasks, as well as specialized capabilities such as Function Calling and structured JSON output. It has been trained to reliably execute function calls and generate JSON responses that follow a specific schema, making it well-suited for applications that require these capabilities. What can I use it for? The Hermes-2-Pro-Mistral-7B-GGUF model can be used for a variety of applications, including: Conversational AI**: The model's strong general language abilities make it suitable for building chatbots and virtual assistants that can engage in natural conversations. Task automation**: The model's Function Calling capabilities can be leveraged to automate various tasks, such as data processing, API integration, and report generation. Data visualization**: The model's ability to generate structured JSON outputs can be used to create data visualization tools and dashboards. Knowledge integration**: The model's broad knowledge base can be used to build applications that require integrating and reasoning over different types of information. Things to try One interesting thing to try with the Hermes-2-Pro-Mistral-7B-GGUF model is to explore its ability to handle multi-turn function calls. By using the provided prompt format, you can engage the model in a structured dialogue where it can execute a series of related function calls to solve more complex problems. This can be particularly useful for building applications that require a high degree of interactivity and task-oriented capabilities. Another interesting aspect to explore is the model's performance on specialized tasks, such as code generation, technical writing, or scientific reasoning. The model's strong language understanding and generation abilities, combined with its structured output capabilities, may make it well-suited for these types of applications.
Updated Invalid Date