submission_id: mistralai-mistral-nemo_9330_v117
developer_uid: immaculate_possum_03470
best_of: 8
celo_rating: 1231.89
display_name: nemo_base_1
family_friendly_score: 0.5772522522522523
family_friendly_standard_error: 0.009061084077235828
formatter: {'memory_template': '<|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 0.95, 'top_p': 1.0, 'min_p': 0.075, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: mistralai/Mistral-Nemo-Instruct-2407
latencies: [{'batch_size': 1, 'throughput': 0.6167079075381272, 'latency_mean': 1.6214534437656403, 'latency_p50': 1.627564787864685, 'latency_p90': 1.7827937126159668}, {'batch_size': 3, 'throughput': 1.0989794607359333, 'latency_mean': 2.7189233231544496, 'latency_p50': 2.732831835746765, 'latency_p90': 3.0156991958618162}, {'batch_size': 5, 'throughput': 1.2422259293196363, 'latency_mean': 4.018422573804855, 'latency_p50': 4.031127214431763, 'latency_p90': 4.500064873695374}, {'batch_size': 6, 'throughput': 1.2636575904852336, 'latency_mean': 4.72177622795105, 'latency_p50': 4.769046068191528, 'latency_p90': 5.30830066204071}, {'batch_size': 8, 'throughput': 1.2659840158042273, 'latency_mean': 6.284705991744995, 'latency_p50': 6.316283583641052, 'latency_p90': 7.119851064682007}, {'batch_size': 10, 'throughput': 1.227434436636583, 'latency_mean': 8.115268539190293, 'latency_p50': 8.200544834136963, 'latency_p90': 9.348991203308104}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: mistralai/Mistral-Nemo-I
model_name: nemo_base_1
model_num_parameters: 12772070400.0
model_repo: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
num_battles: 3028
num_wins: 1422
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.22
timestamp: 2024-09-26T21:00:16+00:00
us_pacific_date: 2024-09-26
win_ratio: 0.46961690885072654
Download Preference Data
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name mistralai-mistral-nemo-9330-v117-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v117-mkmlizer to finish
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║     _____            __           __                                ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║       /___/                                                         ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  Version: 0.11.12                                                   ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  belonging to:                                                      ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v117-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v117-mkmlizer: ║     _____            __           __                                ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║       /___/                                                         ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  Version: 0.11.12                                                   ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  https://mk1.ai                                                     ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  belonging to:                                                      ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v117-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: Downloaded to shared memory in 55.340s
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp7n7g63ba, device:0
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v117-mkmlizer: Downloaded to shared memory in 54.464s
mistralai-mistral-nemo-9330-v117-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp35h6tuz2, device:0
mistralai-mistral-nemo-9330-v117-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: 
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Traceback (most recent call last):
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     cli()
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     return self.main(*args, **kwargs)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     rv = self.invoke(ctx)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     return __callback(*args, **kwargs)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     flywheel.instrument(
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 96, in instrument
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     tokenizer = AutoTokenizer.from_pretrained(input_model_path, verbose=False)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 897, in from_pretrained
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2271, in from_pretrained
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     return cls._from_pretrained(
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2505, in _from_pretrained
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     tokenizer = cls(*init_inputs, **init_kwargs)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/transformers/tokenization_utils_fast.py", line 115, in __init__
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer:     fast_tokenizer = TokenizerFast.from_file(fast_tokenizer_file)
chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer: Exception: data did not match any variant of untagged enum ModelWrapper at line 1217953 column 3
Job chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer completed after 115.28s with status: failed
Stopping job with name chaiml-0926-nemo-virgo-t-3956-v3-mkmlizer
clean up pipeline due to error=%s
Shutdown handler de-registered
MKMLizerError('')
chaiml-0926-nemo-virgo-t_3956_v3 status is now failed due to DeploymentManager action
mistralai-mistral-nemo-9330-v117-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v117/flywheel_model.0.safetensors
mistralai-mistral-nemo-9330-v117-mkmlizer: 
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Job mistralai-mistral-nemo-9330-v117-mkmlizer completed after 141.25s with status: succeeded
Stopping job with name mistralai-mistral-nemo-9330-v117-mkmlizer
Pipeline stage MKMLizer completed in 141.61s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.08s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service mistralai-mistral-nemo-9330-v117
Waiting for inference service mistralai-mistral-nemo-9330-v117 to be ready
admin requested tearing down of zonemercy-vingt-deux-v5_9923_v13
Shutdown handler not registered because Python interpreter is not running in the main thread
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Running pipeline stage MKMLDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLDeleter completed in 0.34s
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Running pipeline stage MKMLModelDeleter
Skipping deletion as no model was successfully uploaded
Pipeline stage MKMLModelDeleter completed in 0.28s
Shutdown handler de-registered
zonemercy-vingt-deux-v5_9923_v13 status is now torndown due to DeploymentManager action
Inference service mistralai-mistral-nemo-9330-v117 ready after 220.5403106212616s
Pipeline stage MKMLDeployer completed in 220.90s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.4418063163757324s
Received healthy response to inference request in 1.705847978591919s
Received healthy response to inference request in 1.9256079196929932s
Received healthy response to inference request in 2.031053066253662s
Received healthy response to inference request in 2.399231195449829s
5 requests
0 failed requests
5th percentile: 1.7497999668121338
10th percentile: 1.7937519550323486
20th percentile: 1.8816559314727783
30th percentile: 1.946696949005127
40th percentile: 1.9888750076293946
50th percentile: 2.031053066253662
60th percentile: 2.178324317932129
70th percentile: 2.3255955696105954
80th percentile: 2.4077462196350097
90th percentile: 2.4247762680053713
95th percentile: 2.433291292190552
99th percentile: 2.4401033115386963
mean time: 2.1007092952728272
Pipeline stage StressChecker completed in 11.28s
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Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 1.94s
Shutdown handler de-registered
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.17s
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Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.16s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service mistralai-mistral-nemo-9330-v117-profiler
Waiting for inference service mistralai-mistral-nemo-9330-v117-profiler to be ready
Inference service mistralai-mistral-nemo-9330-v117-profiler ready after 220.50818610191345s
Pipeline stage MKMLProfilerDeployer completed in 220.97s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/mistralai-mistral-neea9c6c439640a5794cda6fbbae0f46bd-deplokztq6:/code/chaiverse_profiler_1727385067 --namespace tenant-chaiml-guanaco
kubectl exec -it mistralai-mistral-neea9c6c439640a5794cda6fbbae0f46bd-deplokztq6 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727385067 && python profiles.py profile --best_of_n 8 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 1024 --output_tokens 64 --summary /code/chaiverse_profiler_1727385067/summary.json'
kubectl exec -it mistralai-mistral-neea9c6c439640a5794cda6fbbae0f46bd-deplokztq6 --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727385067/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1152.22s
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Running pipeline stage MKMLProfilerDeleter
Checking if service mistralai-mistral-nemo-9330-v117-profiler is running
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Pipeline stage MKMLProfilerDeleter completed in 2.48s
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Pipeline stage MKMLDeleter completed in 126.72s
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Pipeline stage ProductionBlendMKMLTemplater completed in 70.86s
Tearing down inference service mistralai-mistral-nemo-9330-v112
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Pipeline stage MKMLDeleter completed in 131.35s
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Pipeline stage MKMLDeleter completed in 129.81s
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Pipeline stage MKMLDeleter completed in 210.82s
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Cleaning model data from S3
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Cleaning model data from model cache
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Cleaning model data from S3
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