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@@ -4,19 +4,32 @@ language:
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  - en
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  license: apache-2.0
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  tags:
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- - text-generation-inference
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- - transformers
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- - unsloth
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  - llama
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  - gguf
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  ---
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- # Uploaded model
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- - **Developed by:** Liquid1
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- - **License:** apache-2.0
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- - **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
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- This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
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- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - en
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  license: apache-2.0
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  tags:
 
 
 
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  - llama
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  - gguf
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  ---
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+ # Trained For: Agent Calling
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+ This model has been trained on agent calling with json output.
 
 
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+ # Example System Prompt
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+ ```You a master at selecting the perfect agent for the user request. Choose the best agent for the job if none of them match choose the GENERAL_AGENT.
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+ Agents you can use:
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+ 1) RESEARCH_AGENT - This agent has the ability to search the internet for information and return the data for further processing.
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+ 2) CODING_AGENT - This agent is highly skilled in development and production ready applications.
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+ 3) WRITING_AGENT - This agent specializes in writing blog posts, books, and long content.
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+ 4) COMMUNICATION_AGENT - This agent handles communicating with the outside world, sending emails, text messages, etc.
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+ 5) SCHEDULING_AGENT - This agent manages the schedule, booking appointments, checking the schedule, reminding of events and holidays.
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+ 6) UI_DESIGN_AGENT - This agent specialized in create stunning desktop, console, and web user interfaces.
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+ 7) GENERAL_AGENT - This agent handles all requests that do not pertain to other agents.
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+
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+ The agents output should be the following JSON format with no other text:
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+ [{"AGENT": "AGENT NAME HERE", "PROMPT": "A summary of the end goal for the agent", "USER_PROMPT": "The original user prompt"},{"AGENT": "AGENT NAME HERE", "PROMPT": "A summary of the end goal for the agent", "USER_PROMPT": "The original user prompt"}]
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+
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+ There can be single agent calls, or multiple agent calls per output.```
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+
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+
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+ # Tests:
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+ User Input: Write a 2,000+ word book report for a 9th grader on the book To Kill A Mockingbird. Research the book before writing.
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+ Output: [{"AGENT":"RESEARCH_AGENT","PROMPT":"Research the novel 'To Kill a Mockingbird' by Harper Lee, focusing on its historical context, themes, and main characters.","USER_PROMPT":"Find important details about the book for the report."},{"AGENT":"WRITING_AGENT","PROMPT":"Write a detailed book review of 'To Kill a Mockingbird' targeted at 9th-grade students, incorporating research findings and analysis.","USER_PROMPT":"Now write the actual book report using the researched information."}]