junhua024-chai-06-full-_78554

developer_uid: junhua024
submission_id: junhua024-chai-06-full-_78554_v2
model_name: junhua024-chai-06-full-_78554_v2
model_group: junhua024/chai_06_full_0
status: torndown
timestamp: 2025-07-17T11:55:48+00:00
num_battles: 6223
num_wins: 3169
celo_rating: 1283.96
family_friendly_score: 0.5472
family_friendly_standard_error: 0.0070394908906823645
submission_type: basic
model_repo: junhua024/chai_06_full_02102_1215
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.5888361635756859, 'latency_mean': 1.698104317188263, 'latency_p50': 1.6903923749923706, 'latency_p90': 1.8610471487045288}, {'batch_size': 3, 'throughput': 1.0688804953079898, 'latency_mean': 2.795455905199051, 'latency_p50': 2.78439998626709, 'latency_p90': 3.067169737815857}, {'batch_size': 5, 'throughput': 1.2730023042357728, 'latency_mean': 3.9031824433803557, 'latency_p50': 3.9093892574310303, 'latency_p90': 4.335747647285461}, {'batch_size': 6, 'throughput': 1.3322867223073325, 'latency_mean': 4.473674911260605, 'latency_p50': 4.470856428146362, 'latency_p90': 5.018320775032043}, {'batch_size': 8, 'throughput': 1.4027607363814945, 'latency_mean': 5.655727256536483, 'latency_p50': 5.6851887702941895, 'latency_p90': 6.399229288101196}, {'batch_size': 10, 'throughput': 1.429250175839296, 'latency_mean': 6.92709542632103, 'latency_p50': 6.941266775131226, 'latency_p90': 7.789247536659241}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-06-full-_78554_v2
is_internal_developer: False
language_model: junhua024/chai_06_full_02102_1215
model_size: 13B
ranking_group: single
throughput_3p7s: 1.25
us_pacific_date: 2025-07-17
win_ratio: 0.5092399164390166
generation_params: {'temperature': 1.0, 'top_p': 0.88, 'min_p': 0.0, 'top_k': 10, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
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 junhua024-chai-06-full-78554-v2-mkmlizer
Waiting for job on junhua024-chai-06-full-78554-v2-mkmlizer to finish
junhua024-chai-06-full-78554-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
junhua024-chai-06-full-78554-v2-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-06-full-78554-v2-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-78554-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-78554-v2-mkmlizer: Downloaded to shared memory in 129.892s
junhua024-chai-06-full-78554-v2-mkmlizer: Checking if junhua024/chai_06_full_02102_1215 already exists in ChaiML
junhua024-chai-06-full-78554-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp4uqbb35c, device:0
junhua024-chai-06-full-78554-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
junhua024-chai-06-full-78554-v2-mkmlizer: quantized model in 32.957s
junhua024-chai-06-full-78554-v2-mkmlizer: Processed model junhua024/chai_06_full_02102_1215 in 162.924s
junhua024-chai-06-full-78554-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-06-full-78554-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-06-full-78554-v2/nvidia
junhua024-chai-06-full-78554-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-06-full-78554-v2/nvidia/config.json
junhua024-chai-06-full-78554-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-06-full-78554-v2/nvidia/special_tokens_map.json
junhua024-chai-06-full-78554-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-06-full-78554-v2/nvidia/tokenizer_config.json
junhua024-chai-06-full-78554-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-06-full-78554-v2/nvidia/tokenizer.json
junhua024-chai-06-full-78554-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-06-full-78554-v2/nvidia/flywheel_model.0.safetensors
junhua024-chai-06-full-78554-v2-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|          | 2/363 [00:00<00:26, 13.84it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:22, 15.91it/s]
Loading 0:   3%|▎         | 11/363 [00:00<00:12, 29.00it/s]
Loading 0:   4%|▍         | 15/363 [00:00<00:11, 30.88it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:13, 25.94it/s]
Loading 0:   6%|▋         | 23/363 [00:00<00:13, 25.81it/s]
Loading 0:   8%|▊         | 29/363 [00:01<00:10, 33.22it/s]
Loading 0:   9%|▉         | 34/363 [00:01<00:10, 30.84it/s]
Loading 0:  10%|█         | 38/363 [00:01<00:10, 30.94it/s]
Loading 0:  12%|█▏        | 42/363 [00:01<00:11, 28.90it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:08, 38.06it/s]
Loading 0:  15%|█▍        | 54/363 [00:01<00:10, 28.64it/s]
Loading 0:  16%|█▋        | 59/363 [00:02<00:09, 30.88it/s]
Loading 0:  18%|█▊        | 65/363 [00:02<00:09, 31.23it/s]
Loading 0:  19%|█▉        | 69/363 [00:02<00:09, 30.51it/s]
Loading 0:  20%|██        | 74/363 [00:02<00:08, 33.20it/s]
Loading 0:  21%|██▏       | 78/363 [00:02<00:08, 33.13it/s]
Loading 0:  23%|██▎       | 82/363 [00:02<00:09, 29.22it/s]
Loading 0:  24%|██▎       | 86/363 [00:02<00:09, 30.78it/s]
Loading 0:  25%|██▌       | 91/363 [00:03<00:08, 31.58it/s]
Loading 0:  27%|██▋       | 97/363 [00:03<00:08, 32.47it/s]
Loading 0:  28%|██▊       | 101/363 [00:03<00:08, 31.44it/s]
Loading 0:  29%|██▉       | 105/363 [00:03<00:08, 29.37it/s]
Loading 0:  31%|███       | 112/363 [00:03<00:06, 37.81it/s]
Loading 0:  32%|███▏      | 117/363 [00:03<00:08, 27.49it/s]
Loading 0:  34%|███▎      | 122/363 [00:04<00:08, 29.80it/s]
Loading 0:  35%|███▌      | 128/363 [00:04<00:07, 32.43it/s]
Loading 0:  36%|███▋      | 132/363 [00:04<00:07, 31.05it/s]
Loading 0:  38%|███▊      | 137/363 [00:04<00:06, 34.61it/s]
Loading 0:  39%|███▉      | 141/363 [00:04<00:06, 35.34it/s]
Loading 0:  40%|███▉      | 145/363 [00:04<00:06, 31.38it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:07, 30.10it/s]
Loading 0:  43%|████▎     | 155/363 [00:04<00:05, 36.61it/s]
Loading 0:  44%|████▍     | 160/363 [00:05<00:05, 34.84it/s]
Loading 0:  45%|████▌     | 164/363 [00:05<00:05, 34.40it/s]
Loading 0:  46%|████▋     | 168/363 [00:05<00:06, 31.33it/s]
Loading 0:  48%|████▊     | 175/363 [00:05<00:04, 40.04it/s]
Loading 0:  50%|████▉     | 180/363 [00:05<00:06, 28.54it/s]
Loading 0:  51%|█████     | 185/363 [00:05<00:05, 29.90it/s]
Loading 0:  53%|█████▎    | 191/363 [00:06<00:05, 30.82it/s]
Loading 0:  54%|█████▎    | 195/363 [00:06<00:05, 29.99it/s]
Loading 0:  55%|█████▌    | 200/363 [00:06<00:04, 34.07it/s]
Loading 0:  56%|█████▌    | 204/363 [00:06<00:04, 34.78it/s]
Loading 0:  57%|█████▋    | 208/363 [00:06<00:05, 30.64it/s]
Loading 0:  58%|█████▊    | 212/363 [00:06<00:05, 29.43it/s]
Loading 0:  60%|██████    | 218/363 [00:06<00:04, 35.36it/s]
Loading 0:  61%|██████▏   | 223/363 [00:07<00:04, 33.31it/s]
Loading 0:  63%|██████▎   | 227/363 [00:07<00:04, 32.83it/s]
Loading 0:  64%|██████▎   | 231/363 [00:07<00:04, 30.50it/s]
Loading 0:  66%|██████▌   | 238/363 [00:07<00:03, 39.31it/s]
Loading 0:  67%|██████▋   | 243/363 [00:07<00:04, 28.93it/s]
Loading 0:  68%|██████▊   | 248/363 [00:07<00:03, 30.87it/s]
Loading 0:  70%|██████▉   | 254/363 [00:08<00:03, 32.27it/s]
Loading 0:  71%|███████   | 258/363 [00:08<00:03, 31.23it/s]
Loading 0:  72%|███████▏  | 263/363 [00:08<00:02, 34.69it/s]
Loading 0:  74%|███████▎  | 267/363 [00:08<00:02, 34.48it/s]
Loading 0:  75%|███████▍  | 271/363 [00:08<00:03, 29.92it/s]
Loading 0:  76%|███████▌  | 275/363 [00:08<00:03, 29.08it/s]
Loading 0:  77%|███████▋  | 281/363 [00:08<00:02, 35.44it/s]
Loading 0:  79%|███████▉  | 286/363 [00:09<00:02, 33.05it/s]
Loading 0:  80%|███████▉  | 290/363 [00:09<00:02, 32.83it/s]
Loading 0:  81%|████████  | 294/363 [00:09<00:02, 30.80it/s]
Loading 0:  82%|████████▏ | 299/363 [00:09<00:01, 34.91it/s]
Loading 0:  83%|████████▎ | 303/363 [00:09<00:01, 30.75it/s]
Loading 0:  85%|████████▍ | 307/363 [00:09<00:01, 29.85it/s]
Loading 0:  86%|████████▌ | 311/363 [00:09<00:01, 29.11it/s]
Loading 0:  87%|████████▋ | 317/363 [00:10<00:01, 30.97it/s]
Loading 0:  88%|████████▊ | 321/363 [00:10<00:01, 29.70it/s]
Loading 0:  90%|████████▉ | 326/363 [00:10<00:01, 33.71it/s]
Loading 0:  91%|█████████ | 330/363 [00:10<00:00, 34.09it/s]
Loading 0:  92%|█████████▏| 334/363 [00:10<00:01, 28.15it/s]
Loading 0:  93%|█████████▎| 338/363 [00:10<00:00, 27.64it/s]
Loading 0:  95%|█████████▍| 344/363 [00:10<00:00, 33.37it/s]
Loading 0:  96%|█████████▌| 349/363 [00:11<00:00, 22.65it/s]
Loading 0:  97%|█████████▋| 352/363 [00:11<00:00, 19.62it/s]
Loading 0:  98%|█████████▊| 357/363 [00:11<00:00, 22.86it/s]
                                                            
Job junhua024-chai-06-full-78554-v2-mkmlizer completed after 191.78s with status: succeeded
Stopping job with name junhua024-chai-06-full-78554-v2-mkmlizer
Pipeline stage MKMLizer completed in 192.72s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.18s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service junhua024-chai-06-full-78554-v2
Waiting for inference service junhua024-chai-06-full-78554-v2 to be ready
Inference service junhua024-chai-06-full-78554-v2 ready after 292.25623416900635s
Pipeline stage MKMLDeployer completed in 292.97s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.358835220336914s
Received healthy response to inference request in 1.5637242794036865s
Received healthy response to inference request in 1.5071196556091309s
Received healthy response to inference request in 1.7180380821228027s
Received healthy response to inference request in 1.515455722808838s
5 requests
0 failed requests
5th percentile: 1.5087868690490722
10th percentile: 1.5104540824890136
20th percentile: 1.5137885093688965
30th percentile: 1.5251094341278075
40th percentile: 1.544416856765747
50th percentile: 1.5637242794036865
60th percentile: 1.625449800491333
70th percentile: 1.6871753215789795
80th percentile: 1.8461975097656251
90th percentile: 2.1025163650512697
95th percentile: 2.230675792694092
99th percentile: 2.3332033348083496
mean time: 1.7326345920562745
Pipeline stage StressChecker completed in 10.23s
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 0.78s
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 1.03s
Shutdown handler de-registered
junhua024-chai-06-full-_78554_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 0.14s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service junhua024-chai-06-full-78554-v2-profiler
Waiting for inference service junhua024-chai-06-full-78554-v2-profiler to be ready
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 3014.53s
Shutdown handler de-registered
junhua024-chai-06-full-_78554_v2 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-06-full-_78554_v2 status is now torndown due to DeploymentManager action
junhua024-chai-06-full-_78554_v2 status is now torndown due to DeploymentManager action