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Running pipeline stage MKMLizer
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Starting job with name chaiml-icld-v1-dpo-v2-mkmlizer
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Waiting for job on chaiml-icld-v1-dpo-v2-mkmlizer to finish
chaiml-icld-v1-dpo-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ██████ ██████ █████ ████ ████ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ░░██████ ██████ ░░███ ███░ ░░███ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ░███░█████░███ ░███ ███ ░███ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ░███░░███ ░███ ░███████ ░███ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ░███ ░░░ ░███ ░███░░███ ░███ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ░███ ░███ ░███ ░░███ ░███ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ █████ █████ █████ ░░████ █████ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ░░░░░ ░░░░░ ░░░░░ ░░░░ ░░░░░ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ Version: 0.30.2 ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ https://mk1.ai ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ belonging to: ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ Chai Research Corp. ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
chaiml-icld-v1-dpo-v2-mkmlizer: ║ ║
chaiml-icld-v1-dpo-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-icld-v1-dpo-v2-mkmlizer: Downloaded to shared memory in 66.269s
chaiml-icld-v1-dpo-v2-mkmlizer: Checking if ChaiML/icld-v1-dpo already exists in ChaiML
chaiml-icld-v1-dpo-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpbynozwuq, device:0
chaiml-icld-v1-dpo-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-icld-v1-dpo-v2-mkmlizer: quantized model in 313.989s
chaiml-icld-v1-dpo-v2-mkmlizer: Processed model ChaiML/icld-v1-dpo in 380.258s
chaiml-icld-v1-dpo-v2-mkmlizer: creating bucket guanaco-mkml-models
chaiml-icld-v1-dpo-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-icld-v1-dpo-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia
chaiml-icld-v1-dpo-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia/config.json
chaiml-icld-v1-dpo-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia/special_tokens_map.json
chaiml-icld-v1-dpo-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia/tokenizer_config.json
chaiml-icld-v1-dpo-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia/tokenizer.json
chaiml-icld-v1-dpo-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia/flywheel_model.1.safetensors
chaiml-icld-v1-dpo-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-icld-v1-dpo-v2/nvidia/flywheel_model.0.safetensors
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Job chaiml-icld-v1-dpo-v2-mkmlizer completed after 459.49s with status: succeeded
Stopping job with name chaiml-icld-v1-dpo-v2-mkmlizer
Pipeline stage MKMLizer completed in 461.21s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-icld-v1-dpo-v2
Waiting for inference service chaiml-icld-v1-dpo-v2 to be ready
Inference service chaiml-icld-v1-dpo-v2 ready after 140.79513931274414s
Pipeline stage MKMLDeployer completed in 141.39s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.112234115600586s
Received healthy response to inference request in 1.693235158920288s
Received healthy response to inference request in 1.5779709815979004s
Received healthy response to inference request in 1.8971664905548096s
Received healthy response to inference request in 1.5975148677825928s
5 requests
0 failed requests
5th percentile: 1.5818797588348388
10th percentile: 1.5857885360717774
20th percentile: 1.5936060905456544
30th percentile: 1.6166589260101318
40th percentile: 1.65494704246521
50th percentile: 1.693235158920288
60th percentile: 1.7748076915740967
70th percentile: 1.8563802242279053
80th percentile: 2.140180015563965
90th percentile: 2.6262070655822756
95th percentile: 2.8692205905914303
99th percentile: 3.063631410598755
mean time: 1.9756243228912354
Pipeline stage StressChecker completed in 11.55s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.66s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 0.69s
Shutdown handler de-registered
chaiml-icld-v1-dpo_v2 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 0.10s
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 6713.71s
Shutdown handler de-registered