mistralai-mistral-nemo_9330

submission_id: mistralai-mistral-nemo_9330_v116
developer_uid: immaculate_possum_03470
best_of: 8
celo_rating: 1242.32
display_name: nemo_base_1
family_friendly_score: 0.5666558546869932
family_friendly_standard_error: 0.00891721348208551
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': 1.0, 'top_p': 1.0, 'min_p': 0.02, 'top_k': 60, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '<|im_end|>'], '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': 0.6140550942784746, 'latency_mean': 1.6284344244003295, 'latency_p50': 1.6225000619888306, 'latency_p90': 1.7849335432052613}, {'batch_size': 3, 'throughput': 1.0888486884030093, 'latency_mean': 2.751009314060211, 'latency_p50': 2.7621023654937744, 'latency_p90': 3.0279653310775756}, {'batch_size': 5, 'throughput': 1.214350848972894, 'latency_mean': 4.0946382451057435, 'latency_p50': 4.105001091957092, 'latency_p90': 4.645279097557068}, {'batch_size': 6, 'throughput': 1.2570807927314815, 'latency_mean': 4.74891531586647, 'latency_p50': 4.7382975816726685, 'latency_p90': 5.423144817352295}, {'batch_size': 8, 'throughput': 1.2439429536841031, 'latency_mean': 6.4052021288871765, 'latency_p50': 6.4048625230789185, 'latency_p90': 7.204611873626709}, {'batch_size': 10, 'throughput': 1.1843407057763682, 'latency_mean': 8.388230978250503, 'latency_p50': 8.480701327323914, 'latency_p90': 9.443838620185852}]
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: 3146
num_wins: 1536
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.19
timestamp: 2024-09-26T20:54:16+00:00
us_pacific_date: 2024-09-26
win_ratio: 0.4882390336935791
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-v116-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v116-mkmlizer to finish
mistralai-mistral-nemo-9330-v116-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v116-mkmlizer: ║     _____            __           __                                ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║       /___/                                                         ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  Version: 0.11.12                                                   ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  https://mk1.ai                                                     ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  belonging to:                                                      ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v116-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v116-mkmlizer: Downloaded to shared memory in 49.345s
mistralai-mistral-nemo-9330-v116-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpxpsixm9a, device:0
mistralai-mistral-nemo-9330-v116-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v116-mkmlizer: quantized model in 35.905s
mistralai-mistral-nemo-9330-v116-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 85.250s
mistralai-mistral-nemo-9330-v116-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v116-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v116-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v116
mistralai-mistral-nemo-9330-v116-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v116/config.json
mistralai-mistral-nemo-9330-v116-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v116/special_tokens_map.json
mistralai-mistral-nemo-9330-v116-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v116/tokenizer_config.json
mistralai-mistral-nemo-9330-v116-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v116/tokenizer.json
mistralai-mistral-nemo-9330-v116-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v116/flywheel_model.0.safetensors
mistralai-mistral-nemo-9330-v116-mkmlizer: 
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Job mistralai-mistral-nemo-9330-v116-mkmlizer completed after 112.61s with status: succeeded
Stopping job with name mistralai-mistral-nemo-9330-v116-mkmlizer
Pipeline stage MKMLizer completed in 113.44s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
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Creating inference service mistralai-mistral-nemo-9330-v116
Waiting for inference service mistralai-mistral-nemo-9330-v116 to be ready
Shutdown handler not registered because Python interpreter is not running in the main thread
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Starting job with name zonemercy-vingt-deux-v5-9923-v14-mkmlizer
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Starting job with name zonemercy-vingt-deux-v5-9923-v15-mkmlizer
Waiting for job on zonemercy-vingt-deux-v5-9923-v15-mkmlizer to finish
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║     _____            __           __                                ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║       /___/                                                         ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  Version: 0.11.12                                                   ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  https://mk1.ai                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║     _____            __           __                                ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  The license key for the current software has been verified as      ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  belonging to:                                                      ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  Chai Research Corp.                                                ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║       /___/                                                         ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  Version: 0.11.12                                                   ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  https://mk1.ai                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  The license key for the current software has been verified as      ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  belonging to:                                                      ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  Chai Research Corp.                                                ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ║                                                                     ║
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: Downloaded to shared memory in 112.234s
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpq7h6v8fm, device:0
zonemercy-vingt-deux-v5-9923-v14-mkmlizer: Saving flywheel model at /dev/shm/model_cache
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: Downloaded to shared memory in 111.142s
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp80kqwaz9, device:0
zonemercy-vingt-deux-v5-9923-v15-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Inference service mistralai-mistral-nemo-9330-v116 ready after 220.56957244873047s
Pipeline stage MKMLDeployer completed in 220.98s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.232489824295044s
Received healthy response to inference request in 1.6076529026031494s
Received healthy response to inference request in 1.8491663932800293s
Received healthy response to inference request in 1.8037302494049072s
Received healthy response to inference request in 1.6688215732574463s
5 requests
0 failed requests
5th percentile: 1.6198866367340088
10th percentile: 1.6321203708648682
20th percentile: 1.656587839126587
30th percentile: 1.6958033084869384
40th percentile: 1.7497667789459228
50th percentile: 1.8037302494049072
60th percentile: 1.821904706954956
70th percentile: 1.840079164505005
80th percentile: 1.9258310794830322
90th percentile: 2.079160451889038
95th percentile: 2.155825138092041
99th percentile: 2.2171568870544434
mean time: 1.8323721885681152
Pipeline stage StressChecker completed in 10.98s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 6.33s
Shutdown handler de-registered
mistralai-mistral-nemo_9330_v116 status is now deployed due to DeploymentManager action
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Pipeline stage MKMLProfilerTemplater completed in 0.14s
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Creating inference service mistralai-mistral-nemo-9330-v116-profiler
Waiting for inference service mistralai-mistral-nemo-9330-v116-profiler to be ready
Inference service mistralai-mistral-nemo-9330-v116-profiler ready after 220.51563096046448s
Pipeline stage MKMLProfilerDeployer completed in 220.92s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/mistralai-mistral-ne8708144744e24d25826bbe10ea0a40a9-deplonfvvt:/code/chaiverse_profiler_1727384684 --namespace tenant-chaiml-guanaco
kubectl exec -it mistralai-mistral-ne8708144744e24d25826bbe10ea0a40a9-deplonfvvt --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727384684 && 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_1727384684/summary.json'
kubectl exec -it mistralai-mistral-ne8708144744e24d25826bbe10ea0a40a9-deplonfvvt --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727384684/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1168.46s
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