40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
"""
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This example demonstrates how to provide tokenized ids as input instead of text prompt
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"""
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import sglang as sgl
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from sglang.srt.hf_transformers_utils import get_tokenizer
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MODEL_PATH = "meta-llama/Llama-3.1-8B-Instruct"
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def main():
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# Sample prompts.
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prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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# Create a sampling params object.
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sampling_params = {"temperature": 0.8, "top_p": 0.95}
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# Tokenize inputs
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tokenizer = get_tokenizer(MODEL_PATH)
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token_ids_list = [tokenizer.encode(prompt) for prompt in prompts]
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# Create an LLM.
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# You can also specify `skip_tokenizer_init=True`, but it requires explicit detokenization at the end
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llm = sgl.Engine(model_path=MODEL_PATH)
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outputs = llm.generate(input_ids=token_ids_list, sampling_params=sampling_params)
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# Print the outputs.
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for prompt, output in zip(prompts, outputs):
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print("===============================")
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print(f"Prompt: {prompt}\nGenerated Text: {output['text']}")
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# The __main__ condition is necessary here because we use "spawn" to create subprocesses
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# Spawn starts a fresh program every time, if there is no __main__, it will run into infinite loop to keep spawning processes from sgl.Engine
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if __name__ == "__main__":
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main()
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