intervitens-mini-magnum-_5180

developer_uid: azuruce
submission_id: intervitens-mini-magnum-_5180_v5
model_name: intervitens-mini-magnum-_5180_v5
model_group: intervitens/mini-magnum-
status: torndown
timestamp: 2024-09-26T02:09:59+00:00
num_battles: 8073
num_wins: 4106
celo_rating: 1266.04
family_friendly_score: 0.5596058903643173
family_friendly_standard_error: 0.005590264021555534
submission_type: basic
model_repo: intervitens/mini-magnum-12b-v1.1
model_architecture: MistralForCausalLM
model_num_parameters: 12772080640.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
latencies: [{'batch_size': 1, 'throughput': 0.6130934778910379, 'latency_mean': 1.6309897458553315, 'latency_p50': 1.6326375007629395, 'latency_p90': 1.809820580482483}, {'batch_size': 3, 'throughput': 1.0846617781067547, 'latency_mean': 2.7581309974193573, 'latency_p50': 2.7558168172836304, 'latency_p90': 3.0139476537704466}, {'batch_size': 5, 'throughput': 1.2292292873212605, 'latency_mean': 4.040248186588287, 'latency_p50': 4.089730501174927, 'latency_p90': 4.537149739265442}, {'batch_size': 6, 'throughput': 1.267941205081575, 'latency_mean': 4.71802634716034, 'latency_p50': 4.724554538726807, 'latency_p90': 5.380533933639526}, {'batch_size': 8, 'throughput': 1.2485100749276192, 'latency_mean': 6.370021374225616, 'latency_p50': 6.447564363479614, 'latency_p90': 7.094241333007812}, {'batch_size': 10, 'throughput': 1.2080629326136512, 'latency_mean': 8.23291711807251, 'latency_p50': 8.211124777793884, 'latency_p90': 9.320386934280394}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: intervitens-mini-magnum-_5180_v5
is_internal_developer: True
language_model: intervitens/mini-magnum-12b-v1.1
model_size: 13B
ranking_group: single
throughput_3p7s: 1.21
us_pacific_date: 2024-09-25
win_ratio: 0.508608943391552
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '<|eot_id|>', '<|end_of_text|>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': '', 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '### Response:\n{bot_name}:', 'truncate_by_message': False}
Resubmit model
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Starting job with name intervitens-mini-magnum-5180-v5-mkmlizer
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admin requested tearing down of marinaraspaghetti-nemomi_1739_v6
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Running pipeline stage MKMLModelDeleter
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Pipeline stage MKMLModelDeleter completed in 0.12s
Shutdown handler de-registered
marinaraspaghetti-nemomi_1739_v6 status is now torndown due to DeploymentManager action
intervitens-mini-magnum-5180-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
intervitens-mini-magnum-5180-v5-mkmlizer: ║     _____            __           __                                ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║       /___/                                                         ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║                                                                     ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  Version: 0.11.12                                                   ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  https://mk1.ai                                                     ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║                                                                     ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  belonging to:                                                      ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║                                                                     ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  Chai Research Corp.                                                ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
intervitens-mini-magnum-5180-v5-mkmlizer: ║                                                                     ║
intervitens-mini-magnum-5180-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Shutdown handler not registered because Python interpreter is not running in the main thread
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Running pipeline stage MKMLizer
Starting job with name sao10k-l3-8b-stheno-v3-2-v5-mkmlizer
Waiting for job on sao10k-l3-8b-stheno-v3-2-v5-mkmlizer to finish
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║     _____            __           __                                ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║       /___/                                                         ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║                                                                     ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  Version: 0.11.12                                                   ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  https://mk1.ai                                                     ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║                                                                     ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  belonging to:                                                      ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║                                                                     ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  Chai Research Corp.                                                ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ║                                                                     ║
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: Downloaded to shared memory in 21.206s
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpn4zjmv17, device:0
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
intervitens-mini-magnum-5180-v5-mkmlizer: Downloaded to shared memory in 35.657s
intervitens-mini-magnum-5180-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmppk7chcgk, device:0
intervitens-mini-magnum-5180-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: quantized model in 26.719s
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: Processed model Sao10K/L3-8B-Stheno-v3.2 in 47.925s
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: creating bucket guanaco-mkml-models
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/sao10k-l3-8b-stheno-v3-2-v5
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/sao10k-l3-8b-stheno-v3-2-v5/config.json
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/sao10k-l3-8b-stheno-v3-2-v5/special_tokens_map.json
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/sao10k-l3-8b-stheno-v3-2-v5/tokenizer_config.json
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/sao10k-l3-8b-stheno-v3-2-v5/tokenizer.json
intervitens-mini-magnum-5180-v5-mkmlizer: quantized model in 35.662s
intervitens-mini-magnum-5180-v5-mkmlizer: Processed model intervitens/mini-magnum-12b-v1.1 in 71.319s
intervitens-mini-magnum-5180-v5-mkmlizer: creating bucket guanaco-mkml-models
intervitens-mini-magnum-5180-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
intervitens-mini-magnum-5180-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/intervitens-mini-magnum-5180-v5
intervitens-mini-magnum-5180-v5-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/intervitens-mini-magnum-5180-v5/config.json
intervitens-mini-magnum-5180-v5-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/intervitens-mini-magnum-5180-v5/special_tokens_map.json
intervitens-mini-magnum-5180-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/intervitens-mini-magnum-5180-v5/tokenizer_config.json
intervitens-mini-magnum-5180-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/intervitens-mini-magnum-5180-v5/tokenizer.json
sao10k-l3-8b-stheno-v3-2-v5-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/sao10k-l3-8b-stheno-v3-2-v5/flywheel_model.0.safetensors
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intervitens-mini-magnum-5180-v5-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/intervitens-mini-magnum-5180-v5/flywheel_model.0.safetensors
intervitens-mini-magnum-5180-v5-mkmlizer: 
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Job intervitens-mini-magnum-5180-v5-mkmlizer completed after 92.78s with status: succeeded
Stopping job with name intervitens-mini-magnum-5180-v5-mkmlizer
Pipeline stage MKMLizer completed in 93.70s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service intervitens-mini-magnum-5180-v5
Waiting for inference service intervitens-mini-magnum-5180-v5 to be ready
Job sao10k-l3-8b-stheno-v3-2-v5-mkmlizer completed after 82.88s with status: succeeded
Stopping job with name sao10k-l3-8b-stheno-v3-2-v5-mkmlizer
Pipeline stage MKMLizer completed in 83.24s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service sao10k-l3-8b-stheno-v3-2-v5
Waiting for inference service sao10k-l3-8b-stheno-v3-2-v5 to be ready
Inference service intervitens-mini-magnum-5180-v5 ready after 210.46234560012817s
Pipeline stage MKMLDeployer completed in 210.99s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.0063576698303223s
Received healthy response to inference request in 2.007730722427368s
Received healthy response to inference request in 1.7218413352966309s
Received healthy response to inference request in 1.763218879699707s
Received healthy response to inference request in 1.5497138500213623s
5 requests
0 failed requests
5th percentile: 1.584139347076416
10th percentile: 1.6185648441314697
20th percentile: 1.6874158382415771
30th percentile: 1.730116844177246
40th percentile: 1.7466678619384766
50th percentile: 1.763218879699707
60th percentile: 1.8604743957519532
70th percentile: 1.957729911804199
80th percentile: 2.0066322803497316
90th percentile: 2.00718150138855
95th percentile: 2.007456111907959
99th percentile: 2.0076758003234865
mean time: 1.8097724914550781
Pipeline stage StressChecker completed in 11.01s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 4.33s
Shutdown handler de-registered
intervitens-mini-magnum-_5180_v5 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.14s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service intervitens-mini-magnum-5180-v5-profiler
Waiting for inference service intervitens-mini-magnum-5180-v5-profiler to be ready
Inference service intervitens-mini-magnum-5180-v5-profiler ready after 220.5653293132782s
Pipeline stage MKMLProfilerDeployer completed in 221.00s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/intervitens-mini-mag259f787ec1e95e361b33b6f42b08487f-deplo5x79q:/code/chaiverse_profiler_1727317188 --namespace tenant-chaiml-guanaco
kubectl exec -it intervitens-mini-mag259f787ec1e95e361b33b6f42b08487f-deplo5x79q --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727317188 && 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_1727317188/summary.json'
kubectl exec -it intervitens-mini-mag259f787ec1e95e361b33b6f42b08487f-deplo5x79q --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727317188/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1162.24s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service intervitens-mini-magnum-5180-v5-profiler is running
Tearing down inference service intervitens-mini-magnum-5180-v5-profiler
Service intervitens-mini-magnum-5180-v5-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.15s
Shutdown handler de-registered
intervitens-mini-magnum-_5180_v5 status is now inactive due to auto deactivation removed underperforming models
intervitens-mini-magnum-_5180_v5 status is now torndown due to DeploymentManager action