junhua024-chai-16-full-12_429

developer_uid: junhua024

submission_id: junhua024-chai-16-full-12_429_v5

model_name: junhua024-chai-16-full-12_429_v5

model_group: junhua024/chai_16_full_1

status: torndown

timestamp: 2025-07-19T21:14:47+00:00

num_battles: 7926

num_wins: 3865

celo_rating: 1270.71

family_friendly_score: 0.5528

family_friendly_standard_error: 0.007031531269929758

submission_type: basic

model_repo: junhua024/chai_16_full_12_o_ffn_1925

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': 0.5900767146900862, 'latency_mean': 1.6945154666900635, 'latency_p50': 1.6889691352844238, 'latency_p90': 1.8919047594070435}, {'batch_size': 3, 'throughput': 1.0497183638823828, 'latency_mean': 2.8492845129966735, 'latency_p50': 2.885039210319519, 'latency_p90': 3.1059576988220217}, {'batch_size': 5, 'throughput': 1.2647300519909304, 'latency_mean': 3.932362817525864, 'latency_p50': 3.909374952316284, 'latency_p90': 4.448108887672424}, {'batch_size': 6, 'throughput': 1.3127917227714168, 'latency_mean': 4.543296461105347, 'latency_p50': 4.570680737495422, 'latency_p90': 5.062512612342834}, {'batch_size': 8, 'throughput': 1.3758105764890276, 'latency_mean': 5.764599925279617, 'latency_p50': 5.78109073638916, 'latency_p90': 6.486451935768128}, {'batch_size': 10, 'throughput': 1.4223505396432918, 'latency_mean': 6.977042795419693, 'latency_p50': 6.945510268211365, 'latency_p90': 7.93341600894928}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: junhua024-chai-16-full-12_429_v5

is_internal_developer: False

language_model: junhua024/chai_16_full_12_o_ffn_1925

model_size: 13B

ranking_group: single

throughput_3p7s: 1.24

us_pacific_date: 2025-07-19

win_ratio: 0.4876356295735554

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-16-full-12-429-v5-mkmlizer
Waiting for job on junhua024-chai-16-full-12-429-v5-mkmlizer to finish
junhua024-chai-16-full-12-429-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
junhua024-chai-16-full-12-429-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-12-429-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-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-16-full-12-429-v5-mkmlizer: Downloaded to shared memory in 115.963s
junhua024-chai-16-full-12-429-v5-mkmlizer: Checking if junhua024/chai_16_full_12_o_ffn_1925 already exists in ChaiML
junhua024-chai-16-full-12-429-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpnn1nk89x, device:0
junhua024-chai-16-full-12-429-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Failed to get response for submission chaiml-nis-qwen32b-sim_98336_v34: HTTPConnectionPool(host='chaiml-nis-qwen32b-sim-98336-v34-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
junhua024-chai-16-full-12-429-v5-mkmlizer: quantized model in 31.905s
junhua024-chai-16-full-12-429-v5-mkmlizer: Processed model junhua024/chai_16_full_12_o_ffn_1925 in 147.988s
junhua024-chai-16-full-12-429-v5-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-16-full-12-429-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-16-full-12-429-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-16-full-12-429-v5/nvidia
junhua024-chai-16-full-12-429-v5-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-16-full-12-429-v5/nvidia/config.json
junhua024-chai-16-full-12-429-v5-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-16-full-12-429-v5/nvidia/special_tokens_map.json
junhua024-chai-16-full-12-429-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-16-full-12-429-v5/nvidia/tokenizer_config.json
junhua024-chai-16-full-12-429-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-16-full-12-429-v5/nvidia/tokenizer.json
junhua024-chai-16-full-12-429-v5-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-16-full-12-429-v5/nvidia/flywheel_model.0.safetensors
junhua024-chai-16-full-12-429-v5-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|          | 2/363 [00:00<00:25, 14.13it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:21, 16.59it/s]
Loading 0:   3%|▎         | 12/363 [00:00<00:12, 28.12it/s]
Loading 0:   5%|▍         | 17/363 [00:00<00:11, 30.33it/s]
Loading 0:   6%|▋         | 23/363 [00:00<00:10, 32.48it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:07, 43.79it/s]
Loading 0:  10%|▉         | 36/363 [00:01<00:09, 32.85it/s]
Loading 0:  11%|█▏        | 41/363 [00:01<00:09, 33.94it/s]
Loading 0:  14%|█▍        | 50/363 [00:01<00:07, 41.60it/s]
Loading 0:  15%|█▌        | 55/363 [00:01<00:08, 34.98it/s]
Loading 0:  16%|█▋        | 59/363 [00:01<00:08, 34.20it/s]
Loading 0:  18%|█▊        | 65/363 [00:01<00:08, 33.86it/s]
Loading 0:  19%|█▉        | 69/363 [00:02<00:08, 32.76it/s]
Loading 0:  21%|██        | 75/363 [00:02<00:08, 33.30it/s]
Loading 0:  22%|██▏       | 80/363 [00:02<00:09, 31.36it/s]
Loading 0:  23%|██▎       | 84/363 [00:02<00:08, 33.05it/s]
Loading 0:  25%|██▌       | 91/363 [00:02<00:07, 35.41it/s]
Loading 0:  27%|██▋       | 97/363 [00:02<00:07, 36.61it/s]
Loading 0:  28%|██▊       | 101/363 [00:02<00:07, 36.64it/s]
Loading 0:  29%|██▉       | 105/363 [00:03<00:07, 34.24it/s]
Loading 0:  31%|███       | 113/363 [00:03<00:06, 41.14it/s]
Loading 0:  33%|███▎      | 118/363 [00:03<00:07, 34.58it/s]
Loading 0:  34%|███▎      | 122/363 [00:03<00:07, 33.51it/s]
Loading 0:  35%|███▌      | 128/363 [00:03<00:06, 34.42it/s]
Loading 0:  36%|███▋      | 132/363 [00:03<00:07, 32.98it/s]
Loading 0:  38%|███▊      | 138/363 [00:04<00:06, 32.99it/s]
Loading 0:  39%|███▉      | 143/363 [00:04<00:06, 32.62it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:06, 33.75it/s]
Loading 0:  43%|████▎     | 156/363 [00:04<00:05, 41.22it/s]
Loading 0:  44%|████▍     | 161/363 [00:04<00:05, 36.85it/s]
Loading 0:  45%|████▌     | 165/363 [00:04<00:05, 35.21it/s]
Loading 0:  47%|████▋     | 169/363 [00:04<00:05, 34.94it/s]
Loading 0:  48%|████▊     | 176/363 [00:05<00:04, 39.16it/s]
Loading 0:  50%|████▉     | 180/363 [00:05<00:05, 31.34it/s]
Loading 0:  51%|█████     | 185/363 [00:05<00:05, 32.81it/s]
Loading 0:  53%|█████▎    | 191/363 [00:05<00:05, 34.34it/s]
Loading 0:  54%|█████▎    | 195/363 [00:05<00:05, 32.89it/s]
Loading 0:  55%|█████▌    | 200/363 [00:05<00:04, 36.52it/s]
Loading 0:  56%|█████▋    | 205/363 [00:05<00:04, 35.39it/s]
Loading 0:  58%|█████▊    | 209/363 [00:06<00:04, 36.29it/s]
Loading 0:  59%|█████▊    | 213/363 [00:06<00:04, 33.90it/s]
Loading 0:  60%|██████    | 218/363 [00:06<00:03, 37.61it/s]
Loading 0:  61%|██████▏   | 223/363 [00:06<00:03, 36.01it/s]
Loading 0:  63%|██████▎   | 227/363 [00:06<00:03, 34.35it/s]
Loading 0:  64%|██████▎   | 231/363 [00:06<00:04, 32.12it/s]
Loading 0:  66%|██████▌   | 238/363 [00:06<00:03, 40.76it/s]
Loading 0:  67%|██████▋   | 243/363 [00:07<00:04, 28.63it/s]
Loading 0:  68%|██████▊   | 248/363 [00:07<00:03, 30.93it/s]
Loading 0:  70%|██████▉   | 254/363 [00:07<00:03, 32.97it/s]
Loading 0:  71%|███████   | 258/363 [00:07<00:03, 31.87it/s]
Loading 0:  72%|███████▏  | 263/363 [00:07<00:02, 35.29it/s]
Loading 0:  74%|███████▎  | 267/363 [00:07<00:02, 34.34it/s]
Loading 0:  75%|███████▍  | 271/363 [00:07<00:02, 30.79it/s]
Loading 0:  76%|███████▌  | 275/363 [00:08<00:02, 29.98it/s]
Loading 0:  77%|███████▋  | 281/363 [00:08<00:02, 36.31it/s]
Loading 0:  79%|███████▉  | 286/363 [00:08<00:02, 34.81it/s]
Loading 0:  80%|███████▉  | 290/363 [00:08<00:02, 34.52it/s]
Loading 0:  81%|████████  | 294/363 [00:08<00:02, 32.50it/s]
Loading 0:  83%|████████▎ | 302/363 [00:08<00:01, 38.77it/s]
Loading 0:  84%|████████▍ | 306/363 [00:08<00:01, 31.09it/s]
Loading 0:  86%|████████▌ | 311/363 [00:09<00:01, 32.60it/s]
Loading 0:  87%|████████▋ | 317/363 [00:09<00:01, 34.24it/s]
Loading 0:  88%|████████▊ | 321/363 [00:09<00:01, 33.02it/s]
Loading 0:  90%|█████████ | 327/363 [00:09<00:01, 33.91it/s]
Loading 0:  91%|█████████▏| 332/363 [00:09<00:00, 33.88it/s]
Loading 0:  93%|█████████▎| 338/363 [00:09<00:00, 34.41it/s]
Loading 0:  95%|█████████▍| 344/363 [00:10<00:00, 38.74it/s]
Loading 0:  96%|█████████▌| 349/363 [00:10<00:00, 26.37it/s]
Loading 0:  97%|█████████▋| 353/363 [00:10<00:00, 23.94it/s]
Loading 0:  98%|█████████▊| 357/363 [00:10<00:00, 25.34it/s]
                                                            
Job junhua024-chai-16-full-12-429-v5-mkmlizer completed after 171.05s with status: succeeded
Stopping job with name junhua024-chai-16-full-12-429-v5-mkmlizer
Pipeline stage MKMLizer completed in 171.67s
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-16-full-12-429-v5
Waiting for inference service junhua024-chai-16-full-12-429-v5 to be ready
Inference service junhua024-chai-16-full-12-429-v5 ready after 321.3370132446289s
Pipeline stage MKMLDeployer completed in 321.85s
run pipeline stage %s
Running pipeline stage StressChecker
HTTPConnectionPool(host='guanaco-submitter.guanaco-backend.k2.chaiverse.com', port=80): Read timed out. (read timeout=20)
Received unhealthy response to inference request!
Received healthy response to inference request in 2.774829626083374s
Received healthy response to inference request in 1.704608678817749s
Received healthy response to inference request in 1.911851406097412s
Received healthy response to inference request in 1.651972770690918s
5 requests
1 failed requests
5th percentile: 1.6624999523162842
10th percentile: 1.6730271339416505
20th percentile: 1.6940814971923828
30th percentile: 1.7460572242736816
40th percentile: 1.828954315185547
50th percentile: 1.911851406097412
60th percentile: 2.2570426940917967
70th percentile: 2.6022339820861813
80th percentile: 6.253076314926151
90th percentile: 13.209569692611696
95th percentile: 16.687816381454464
99th percentile: 19.470413732528687
mean time: 5.6418651103973385
%s, retrying in %s seconds...
Received healthy response to inference request in 1.9122560024261475s
Received healthy response to inference request in 2.1101207733154297s
Received healthy response to inference request in 1.8512895107269287s
Received healthy response to inference request in 2.101806640625s
Received healthy response to inference request in 2.040525197982788s
5 requests
0 failed requests
5th percentile: 1.8634828090667725
10th percentile: 1.8756761074066162
20th percentile: 1.9000627040863036
30th percentile: 1.9379098415374756
40th percentile: 1.9892175197601318
50th percentile: 2.040525197982788
60th percentile: 2.0650377750396727
70th percentile: 2.0895503520965577
80th percentile: 2.103469467163086
90th percentile: 2.1067951202392576
95th percentile: 2.1084579467773437
99th percentile: 2.1097882080078123
mean time: 2.0031996250152586
Pipeline stage StressChecker completed in 41.08s
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 0.69s
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 1.55s
Shutdown handler de-registered
junhua024-chai-16-full-12_429_v5 status is now deployed due to DeploymentManager action
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
Pipeline stage OfflineFamilyFriendlyScorer completed in 4948.60s
Shutdown handler de-registered
junhua024-chai-16-full-12_429_v5 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-16-full-12_429_v5 status is now torndown due to DeploymentManager action