Instructions to use TitanML/Qwen-7B-Chat-Int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use TitanML/Qwen-7B-Chat-Int8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TitanML/Qwen-7B-Chat-Int8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitanML/Qwen-7B-Chat-Int8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TitanML/Qwen-7B-Chat-Int8
- SGLang
How to use TitanML/Qwen-7B-Chat-Int8 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TitanML/Qwen-7B-Chat-Int8" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitanML/Qwen-7B-Chat-Int8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "TitanML/Qwen-7B-Chat-Int8" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitanML/Qwen-7B-Chat-Int8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TitanML/Qwen-7B-Chat-Int8 with Docker Model Runner:
docker model run hf.co/TitanML/Qwen-7B-Chat-Int8
Update README.md
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pipeline_tag: text-generation
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inference: false
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# Qwen-7B-Chat-Int8
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如果你想给我们的研发团队和产品团队留言,欢迎加入我们的微信群、钉钉群以及Discord!同时,也欢迎通过邮件(qianwen_opensource@alibabacloud.com)联系我们。
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If you are interested to leave a message to either our research team or product team, join our Discord or WeChat groups! Also, feel free to send an email to qianwen_opensource@alibabacloud.com.
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pipeline_tag: text-generation
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inference: false
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base_model:
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- Qwen/Qwen-7B-Chat
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# Qwen-7B-Chat-Int8
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如果你想给我们的研发团队和产品团队留言,欢迎加入我们的微信群、钉钉群以及Discord!同时,也欢迎通过邮件(qianwen_opensource@alibabacloud.com)联系我们。
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If you are interested to leave a message to either our research team or product team, join our Discord or WeChat groups! Also, feel free to send an email to qianwen_opensource@alibabacloud.com.
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