#!/usr/bin/env python3 """Minimal classify demo using token IDs as input. This mirrors the docs example: llm = LLM(model="...", runner="pooling") (output,) = llm.classify("Hello, my name is") but feeds DEFAULT_PROMPT_TOKEN_IDS via token_inputs instead of text. """ from vllm import LLM from vllm.inputs import token_inputs DEFAULT_PROMPT_TOKEN_IDS = [ 127958, 58, 10172, 24575, 8437, 7489, 51, 60, 220, 57668, 102832, 80073, 75761, 102245, 39045, 57668, 105982, 103429, 88852, 9743, 34208, 2929, 3922, 101423, 83125, 110357, 107759, 82317, 101505, 101009, 1811, 15225, 61633, 3922, 101992, 80073, 120702, 17, 15, 17, 19, 8107, 16, 17, 9953, 17, 17, 9080, 3490, 2929, 5232, 82, 8910, 6704, 25451, 43032, 198, 12, 11615, 101241, 5232, 101016, 198, 12, 220, 104780, 101526, 5232, 43292, 104780, 198, 12, 61696, 225, 101028, 101526, 5232, 16325, 106444, 271, 9743, 44915, 29411, 12, 52561, 229, 34972, 5232, 11144, 19378, 101814, 106742, 11199, 19378, 100904, 101130, 198, 12, 73028, 96, 17161, 5232, 83125, 25580, 78244, 105996, 119022, 117130, 103702, 101021, 28542, 104156, 101526, 100765, 5486, 101526, 112370, 101526, 107717, 101026, 3922, 101093, 101406, 102193, 92780, 105328, 102715, 101697, 99480, 71600, 101026, 69636, 105219, 33764, 83800, 100502, 78698, 101300, 83800, 100476, 105259, 106329, 69636, 106536, 124213, 100893, 9554, 108473, 3922, 78657, 5232, 100588, 105219, 33764, 100502, 79656, 106555, 116251, 97150, 83800, 101697, 99480, 101026, 16325, 106246, 106408, 20600, 100580, 20675, 28469, 121838, 72917, 113081, 113633, 108149, 103463, 69636, 103575, 100614, 100860, 70616, 115163, 100886, 83800, 102674, 17297, 101006, 105740, 26016, 100588, 83800, 29391, 41401, 121110, 105278, 30046, 111058, 105278, 102341, 73548, 101987, 101995, 38129, 69636, 110858, 102674, 17297, 44368, 72917, 110991, 105529, 50667, 3922, 101374, 114621, 83800, 106773, 34547, 101356, 107000, 106212, 87219, 69636, 103575, 113429, 102072, 21082, 101593, 106874, 19378, 51611, 91940, 113846, 1811, 19378, 101924, 19378, 3844, 18936, 11050, 75492, 3922, 100502, 100632, 117130, 8, 105299, 109665, 101657, 105148, 46281, 100502, 102172, 101420, 119022, 106334, 101393, 3922, 100582, 100486, 123002, 105996, 119022, 117130, 9554, 104090, 101909, 100746, 102900, 103394, 106212, 100639, 37507, 101745, 34208, 101364, 83800, 106368, 100502, 100943, 19378, 115256, 35304, 119022, 109364, 100502, 101792, 101025, 3922, 107105, 100632, 20834, 108149, 102715, 51611, 271, 9743, 58521, 29411, 482, 220, 58521, 31091, 5232, 100655, 104091, 78519, 105689, 198, 482, 220, 58521, 101241, 5232, 100827, 62, 107940, 198, 482, 220, 58521, 105302, 5232, 100580, 271, 9743, 90261, 5232, 106425, 32239, 198, 482, 75677, 111, 55038, 101241, 5232, 100992, 111155, 198, 482, 41766, 229, 81742, 33005, 5232, 100359, 198, 482, 75677, 111, 55038, 105344, 5232, 16, 15, 198, 482, 61696, 225, 101028, 105344, 5232, 16, 271, 9743, 21082, 5232, 17, 15, 17, 18, 8107, 15, 18, 9953, 15, 20, 9080, 320, 101396, 37271, 5232, 21, 20, 23, 36827, 696, 2929, 5232, 82, 8910, 6704, 25451, 43032, 127962, 127960, 127967, ] if __name__ == "__main__": llm = LLM(model="/tools/gy_model/hunyuan_model", task="classify",trust_remote_code=True,runner="pooling") (output,) = llm.classify(token_inputs(DEFAULT_PROMPT_TOKEN_IDS)) probs = output.outputs.probs print(f"Class Probabilities: {probs!r} (size={len(probs)})")