AI Model Deployment: From Dev to Production
AI Model Deployment: From Dev to Production
💡 What You Will Learn
AI Model Deployment: From Dev to Production
ollama run qwen2.5:7b
# Auto/Automatic localhost:11434 OpenAI API
curl http://localhost:11434/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{"model":"qwen2.5:7b","messages":[{"role":"user","content":""}]}'
pip install vllm
python -m vllm.entrypoints.openai.api_server \
--model Qwen/Qwen2.5-7B-Instruct \
--tensor-parallel-size 1 \
--max-model-len 8192 \
--gpu-memory-utilization 0.9
FROM vllm/vllm-openai:latest
|:----|:-------:|:-------:|:---:|:--------| | Ollama || ~500 t/s ||| | vLLM || ~2400 t/s |||
Related Articles
2026-07-19
AnythingLLM Tutorial: Manage All AI Models in One Interface
2026-08-03
How LLMs Actually Work 2026: NanoGPT (62k Stars) - Build GPT From Scratch and Truly Understand It
2026-07-17
AI Agent Feature Flag Deploy 2026
Written by our editorial team; tools listed here are tested or verified against public sources. Links point to official sites or GitHub repos for reference only โ no paid placements.
