docs: Add DeepSeek tutorial #128
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| ``` | ||
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| The following steps should result in a `results.txt` that has the following content | ||
| ```bash |
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nit: This is just text and not bash
ziqifan617
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Jan 31, 2025
krishung5
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Jan 31, 2025
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| ```bash | ||
| $ curl -X POST localhost:8000/v2/models/vllm_model/generate -d '{"text_input": "What is Triton Inference Server?", "parameters": {"stream": false, n"temperature": 0, "exclude_input_in_output": true, "max_tokens": 45}}' | jq | ||
| { | ||
| "model_name": "vllm_model", | ||
| "model_version": "1", | ||
| "text_output": " It's a high-performance, scalable, and efficient inference server for AI models. It's designed to handle large numbers of requests quickly and efficiently, making it suitable for real-time applications like autonomous vehicles, smart homes, and more" | ||
| } | ||
| ``` |
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nit: Could we separate the bash command and the output log? I think this would be easier for users to quickly copy paste the command:
curl -X POST localhost:8000/v2/models/vllm_model/generate -d '{"text_input": "What is Triton Inference Server?", "parameters": {"stream": false, n"temperature": 0, "exclude_input_in_output": true, "max_tokens": 45}}' | jqThen you should see the output
{
"model_name": "vllm_model",
"model_version": "1",
"text_output": " It's a high-performance, scalable, and efficient inference server for AI models. It's designed to handle large numbers of requests quickly and efficiently, making it suitable for real-time applications like autonomous vehicles, smart homes, and more"
}
krishung5
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Jan 31, 2025
rmccorm4
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Jan 31, 2025
Review 1 Co-authored-by: pranavm-nvidia <[email protected]> Co-authored-by: Kris Hung <[email protected]> Co-authored-by: Ryan McCormick <[email protected]>
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statiraju
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statiraju
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Feb 3, 2025
|
Thanks for the quick guide @oandreeva-nv |
statiraju
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* Deepseek tutorial --------- Co-authored-by: pranavm-nvidia <[email protected]> Co-authored-by: Kris Hung <[email protected]> Co-authored-by: Ryan McCormick <[email protected]>
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