submission_id: jic062-nemo-v1-2_v1
developer_uid: chace9580
alignment_samples: 14719
alignment_score: 0.369384661873089
best_of: 8
celo_rating: 1257.43
display_name: jic062-nemo-v1-2_v1
formatter: {'memory_template': '[INST]system\n{memory}[/INST]\n', 'prompt_template': '[INST]user\n{prompt}[/INST]\n', 'bot_template': '[INST]assistant\n{bot_name}: {message}[/INST]\n', 'user_template': '[INST]user\n{user_name}: {message}[/INST]\n', 'response_template': '[INST]assistant\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 0.75, 'top_p': 1.0, 'min_p': 0.1, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '\n\n', '\nYou:', '[/INST]', '<|im_end|>', '</s>'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: jic062/Nemo-v1.2
latencies: [{'batch_size': 1, 'throughput': 0.6844549025765424, 'latency_mean': 1.460957601070404, 'latency_p50': 1.461259365081787, 'latency_p90': 1.618291449546814}, {'batch_size': 3, 'throughput': 1.3196511287231076, 'latency_mean': 2.261894677877426, 'latency_p50': 2.2573232650756836, 'latency_p90': 2.5306148529052734}, {'batch_size': 5, 'throughput': 1.5616921695772603, 'latency_mean': 3.1873308861255647, 'latency_p50': 3.189086675643921, 'latency_p90': 3.582643675804138}, {'batch_size': 6, 'throughput': 1.6054549973322825, 'latency_mean': 3.720084156990051, 'latency_p50': 3.7634326219558716, 'latency_p90': 4.202585077285766}, {'batch_size': 8, 'throughput': 1.5920524640664568, 'latency_mean': 4.998916575908661, 'latency_p50': 5.011911630630493, 'latency_p90': 5.686991882324219}, {'batch_size': 10, 'throughput': 1.5395330771273237, 'latency_mean': 6.468786809444428, 'latency_p50': 6.48987078666687, 'latency_p90': 7.36030490398407}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: jic062/Nemo-v1.2
model_name: jic062-nemo-v1-2_v1
model_num_parameters: 12772070400.0
model_repo: jic062/Nemo-v1.2
model_size: 13B
num_battles: 14718
num_wins: 7681
propriety_score: 0.746177370030581
propriety_total_count: 1308.0
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.61
timestamp: 2024-09-03T19:48:29+00:00
us_pacific_date: 2024-09-03
win_ratio: 0.5218779725506183
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name jic062-nemo-v1-2-v1-mkmlizer
Waiting for job on jic062-nemo-v1-2-v1-mkmlizer to finish
Stopping job with name jic062-nemo-v1-2-v1-mkmlizer
%s, retrying in %s seconds...
Starting job with name jic062-nemo-v1-2-v1-mkmlizer
Waiting for job on jic062-nemo-v1-2-v1-mkmlizer to finish
jic062-nemo-v1-2-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
jic062-nemo-v1-2-v1-mkmlizer: ║     _____            __           __                                ║
jic062-nemo-v1-2-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
jic062-nemo-v1-2-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
jic062-nemo-v1-2-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
jic062-nemo-v1-2-v1-mkmlizer: ║       /___/                                                         ║
jic062-nemo-v1-2-v1-mkmlizer: ║                                                                     ║
jic062-nemo-v1-2-v1-mkmlizer: ║  Version: 0.10.1                                                    ║
jic062-nemo-v1-2-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
jic062-nemo-v1-2-v1-mkmlizer: ║  https://mk1.ai                                                     ║
jic062-nemo-v1-2-v1-mkmlizer: ║                                                                     ║
jic062-nemo-v1-2-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
jic062-nemo-v1-2-v1-mkmlizer: ║  belonging to:                                                      ║
jic062-nemo-v1-2-v1-mkmlizer: ║                                                                     ║
jic062-nemo-v1-2-v1-mkmlizer: ║  Chai Research Corp.                                                ║
jic062-nemo-v1-2-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
jic062-nemo-v1-2-v1-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
jic062-nemo-v1-2-v1-mkmlizer: ║                                                                     ║
jic062-nemo-v1-2-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Connection pool is full, discarding connection: %s. Connection pool size: %s
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jic062-nemo-v1-2-v1-mkmlizer: Downloaded to shared memory in 54.098s
jic062-nemo-v1-2-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmplqzp_vvw, device:0
jic062-nemo-v1-2-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
jic062-nemo-v1-2-v1-mkmlizer: quantized model in 36.150s
jic062-nemo-v1-2-v1-mkmlizer: Processed model jic062/Nemo-v1.2 in 90.249s
jic062-nemo-v1-2-v1-mkmlizer: creating bucket guanaco-mkml-models
jic062-nemo-v1-2-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jic062-nemo-v1-2-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jic062-nemo-v1-2-v1
jic062-nemo-v1-2-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v1/special_tokens_map.json
jic062-nemo-v1-2-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v1/config.json
jic062-nemo-v1-2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v1/tokenizer_config.json
jic062-nemo-v1-2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v1/tokenizer.json
jic062-nemo-v1-2-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/jic062-nemo-v1-2-v1/flywheel_model.0.safetensors
jic062-nemo-v1-2-v1-mkmlizer: 
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Job jic062-nemo-v1-2-v1-mkmlizer completed after 115.62s with status: succeeded
Stopping job with name jic062-nemo-v1-2-v1-mkmlizer
Pipeline stage MKMLizer completed in 117.05s
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Creating inference service jic062-nemo-v1-2-v1
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Inference service jic062-nemo-v1-2-v1 ready after 141.51919770240784s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.266494035720825s
Received healthy response to inference request in 2.2948901653289795s
Received healthy response to inference request in 1.7018852233886719s
Received healthy response to inference request in 1.8444621562957764s
Received healthy response to inference request in 2.1009535789489746s
5 requests
0 failed requests
5th percentile: 1.7304006099700928
10th percentile: 1.7589159965515138
20th percentile: 1.8159467697143554
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40th percentile: 1.9983570098876953
50th percentile: 2.1009535789489746
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70th percentile: 2.233385944366455
80th percentile: 2.272173261642456
90th percentile: 2.2835317134857176
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99th percentile: 2.2937543201446533
mean time: 2.0417370319366457
Pipeline stage StressChecker completed in 10.89s
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Running pipeline stage TriggerMKMLProfilingPipeline
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jic062-nemo-v1-2_v1 status is now deployed due to DeploymentManager action
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Inference service jic062-nemo-v1-2-v1-profiler ready after 150.35003471374512s
Pipeline stage MKMLProfilerDeployer completed in 150.78s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-nemo-v1-2-v1-profiler-predictor-00001-deployment-672mkpf:/code/chaiverse_profiler_1725393396 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-nemo-v1-2-v1-profiler-predictor-00001-deployment-672mkpf --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725393396 && 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 512 --output_tokens 64 --summary /code/chaiverse_profiler_1725393396/summary.json'
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Running pipeline stage MKMLProfilerDeleter
Checking if service jic062-nemo-v1-2-v1-profiler is running
Tearing down inference service jic062-nemo-v1-2-v1-profiler
Service jic062-nemo-v1-2-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.59s
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Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.15s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service jic062-nemo-v1-2-v1-profiler
Waiting for inference service jic062-nemo-v1-2-v1-profiler to be ready
Inference service jic062-nemo-v1-2-v1-profiler ready after 60.21142053604126s
Pipeline stage MKMLProfilerDeployer completed in 60.60s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-nemo-v1-2-v1-profiler-predictor-00001-deployment-5b8zntj:/code/chaiverse_profiler_1725395555 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-nemo-v1-2-v1-profiler-predictor-00001-deployment-5b8zntj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725395555 && chmod +x profiles.py && 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 512 --output_tokens 64 --summary /code/chaiverse_profiler_1725395555/summary.json'
kubectl exec -it jic062-nemo-v1-2-v1-profiler-predictor-00001-deployment-5b8zntj --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725395555/summary.json'
Pipeline stage MKMLProfilerRunner completed in 958.28s
cleanup pipeline after completion
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Running pipeline stage MKMLProfilerDeleter
Checking if service jic062-nemo-v1-2-v1-profiler is running
Tearing down inference service jic062-nemo-v1-2-v1-profiler
Service jic062-nemo-v1-2-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.75s
jic062-nemo-v1-2_v1 status is now inactive due to auto deactivation removed underperforming models

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