Mistral 7B Instruct V0.3 API
Released July 2024 | 32K Tokens context | 7.3B params parameters
Mistral 7B Instruct V0.3 API enables Chatbots, Content generation, Code assistance, Question answering, and Summarization. Mistral 7B is a 7.3B parameter language model celebrated for its efficiency, outperforming larger models on many benchmarks. The v0.3 instruct version is specifically fine-tuned for chat and instruction-following tasks. Standout strengths include Fast inference speed and Low memory footprint. It is optimized for production agent and assistant workloads where response quality, latency, and predictable operating cost all matter.
from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="mistralai/Mistral-7B-Instruct-v0.3", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.7, top_p=1, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n")from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="mistralai/Mistral-7B-Instruct-v0.3", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.7, top_p=1, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n") Enterprise
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