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https://github.com/NVIDIA/TensorRT-LLM.git
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45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
import os
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import subprocess
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import sys
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PROMPT = "Tell a story"
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LLAMA_MODEL_DIR = sys.argv[1]
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TMP_ENGINE_DIR = sys.argv[2] if len(sys.argv) > 2 else "./tllm.engine.example"
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EXAMPLES_ROOT = sys.argv[3] if len(sys.argv) > 3 else ""
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LLM_EXAMPLES = os.path.join(EXAMPLES_ROOT, 'llm_examples.py')
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run_cmd = [
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sys.executable, LLM_EXAMPLES, "--task=run_llm_from_huggingface_model",
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f"--prompt={PROMPT}", f"--hf_model_dir={LLAMA_MODEL_DIR}",
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f"--dump_engine_dir={TMP_ENGINE_DIR}"
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]
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subprocess.run(run_cmd, check=True)
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# TP enabled
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run_cmd = [
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sys.executable, LLM_EXAMPLES, "--task=run_llm_from_huggingface_model",
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f"--prompt={PROMPT}", f"--hf_model_dir={LLAMA_MODEL_DIR}", "--tp_size=2"
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]
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subprocess.run(run_cmd, check=True)
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run_cmd = [
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sys.executable, LLM_EXAMPLES, "--task=run_llm_from_tllm_engine",
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f"--prompt={PROMPT}", f"--hf_model_dir={LLAMA_MODEL_DIR}",
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f"--dump_engine_dir={TMP_ENGINE_DIR}"
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]
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subprocess.run(run_cmd, check=True)
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run_cmd = [
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sys.executable, LLM_EXAMPLES, "--task=run_llm_generate_async_example",
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f"--prompt={PROMPT}", f"--hf_model_dir={LLAMA_MODEL_DIR}"
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]
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subprocess.run(run_cmd, check=True)
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# Both TP and streaming enabled
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run_cmd = [
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sys.executable, LLM_EXAMPLES, "--task=run_llm_generate_async_example",
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f"--prompt={PROMPT}", f"--hf_model_dir={LLAMA_MODEL_DIR}", "--streaming",
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"--tp_size=2"
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]
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subprocess.run(run_cmd, check=True)
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