Airoboros 70B
The Airoboros Llama 2 70B model is fine-tuned using synthetic data from the Airoboros dataset. It focuses on instruction following and contextual question answering tasks. It aims to provide longer and context-compliant responses while ensuring minimal hallucinations. Researchers can explore various prompts formats like obedient question-answering, summarization, coding instructions, agent/function calling, chain-of-thought scenarios, and reWOO style execution planning to leverage the model's capabilities. With a thorough emphasis on generating optimal responses, the model supports sophisticated execution planning for complex tasks using a range of available tools.
main.py
from openai import OpenAI client = OpenAI( base_url="https://api.respan.ai/api/", api_key="YOUR_RESPAN_API_KEY",) response = client.chat.completions.create( model="openrouter/jondurbin/airoboros-l2-70b", messages=[{"role": "user", "content": "Hello!"}],)print(response.choices[0].message.content)from openai import OpenAI client = OpenAI( base_url="https://api.respan.ai/api/", api_key="YOUR_RESPAN_API_KEY",) response = client.chat.completions.create( model="openrouter/jondurbin/airoboros-l2-70b", messages=[{"role": "user", "content": "Hello!"}],)print(response.choices[0].message.content)Providers
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