developer_uid: RandomForest1024
submission_id: albertwang8192-2025-07-04-1_v1
model_name: 2025-07-04_1
model_group: AlbertWang8192/2025-07-0
status: torndown
timestamp: 2025-07-04T21:58:36+00:00
num_battles: 8964
num_wins: 4004
celo_rating: 1248.72
family_friendly_score: 0.598
family_friendly_standard_error: 0.0069339166421294686
submission_type: basic
model_repo: AlbertWang8192/2025-07-04_1
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': 0.5931350230706367, 'latency_mean': 1.6857739198207855, 'latency_p50': 1.6836572885513306, 'latency_p90': 1.863522458076477}, {'batch_size': 3, 'throughput': 1.075088806722269, 'latency_mean': 2.783372827768326, 'latency_p50': 2.7732139825820923, 'latency_p90': 3.0507065057754517}, {'batch_size': 5, 'throughput': 1.2884027109972453, 'latency_mean': 3.855932252407074, 'latency_p50': 3.850360155105591, 'latency_p90': 4.229205131530762}, {'batch_size': 6, 'throughput': 1.3503729375051459, 'latency_mean': 4.420798218250274, 'latency_p50': 4.386953711509705, 'latency_p90': 4.92019031047821}, {'batch_size': 8, 'throughput': 1.4227808013758494, 'latency_mean': 5.584187322854996, 'latency_p50': 5.620149374008179, 'latency_p90': 6.334722638130188}, {'batch_size': 10, 'throughput': 1.4380140335780156, 'latency_mean': 6.897036910057068, 'latency_p50': 6.919816493988037, 'latency_p90': 7.709710741043091}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: 2025-07-04_1
is_internal_developer: False
language_model: AlbertWang8192/2025-07-04_1
model_size: 13B
ranking_group: single
throughput_3p7s: 1.27
us_pacific_date: 2025-07-04
win_ratio: 0.4466755912539045
generation_params: {'temperature': 0.6, 'top_p': 0.95, 'min_p': 0.025, 'top_k': 60, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['\n', '<|im_end|>', '<|im_start|>'], '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 albertwang8192-2025-07-04-1-v1-mkmlizer
Waiting for job on albertwang8192-2025-07-04-1-v1-mkmlizer to finish
albertwang8192-2025-07-04-1-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
albertwang8192-2025-07-04-1-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-04-1-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-04-1-v1-mkmlizer: Downloaded to shared memory in 80.016s
albertwang8192-2025-07-04-1-v1-mkmlizer: Checking if AlbertWang8192/2025-07-04_1 already exists in ChaiML
albertwang8192-2025-07-04-1-v1-mkmlizer: Creating repo ChaiML/2025-07-04_1 and uploading /tmp/tmpz9s1txs3 to it
albertwang8192-2025-07-04-1-v1-mkmlizer: 
  0%|          | 0/11 [00:00<?, ?it/s]
  9%|▉         | 1/11 [00:04<00:43,  4.30s/it]
 18%|█▊        | 2/11 [00:11<00:51,  5.73s/it]
 27%|██▋       | 3/11 [00:14<00:37,  4.73s/it]
 36%|███▋      | 4/11 [00:22<00:43,  6.15s/it]
 45%|████▌     | 5/11 [00:31<00:41,  6.86s/it]
 55%|█████▍    | 6/11 [00:36<00:31,  6.36s/it]
 64%|██████▎   | 7/11 [00:41<00:23,  5.80s/it]
 73%|███████▎  | 8/11 [00:44<00:15,  5.07s/it]
 82%|████████▏ | 9/11 [00:48<00:09,  4.81s/it]
 91%|█████████ | 10/11 [00:55<00:05,  5.42s/it]
100%|██████████| 11/11 [00:56<00:00,  4.14s/it]
100%|██████████| 11/11 [00:56<00:00,  5.17s/it]
albertwang8192-2025-07-04-1-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpz9s1txs3, device:0
albertwang8192-2025-07-04-1-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-04-1-v1-mkmlizer: quantized model in 37.790s
albertwang8192-2025-07-04-1-v1-mkmlizer: Processed model AlbertWang8192/2025-07-04_1 in 223.360s
albertwang8192-2025-07-04-1-v1-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-04-1-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-04-1-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-04-1-v1/nvidia
albertwang8192-2025-07-04-1-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-1-v1/nvidia/config.json
albertwang8192-2025-07-04-1-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-1-v1/nvidia/special_tokens_map.json
albertwang8192-2025-07-04-1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-1-v1/nvidia/tokenizer_config.json
albertwang8192-2025-07-04-1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-1-v1/nvidia/tokenizer.json
albertwang8192-2025-07-04-1-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-04-1-v1/nvidia/flywheel_model.0.safetensors
albertwang8192-2025-07-04-1-v1-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:16, 21.81it/s]
Loading 0:   3%|▎         | 10/363 [00:00<00:12, 27.54it/s]
Loading 0:   4%|▍         | 14/363 [00:00<00:14, 24.05it/s]
Loading 0:   6%|▌         | 21/363 [00:00<00:09, 34.70it/s]
Loading 0:   7%|▋         | 25/363 [00:01<00:15, 22.47it/s]
Loading 0:   8%|▊         | 28/363 [00:01<00:14, 22.37it/s]
Loading 0:   9%|▉         | 32/363 [00:01<00:15, 21.39it/s]
Loading 0:  11%|█         | 39/363 [00:01<00:11, 28.08it/s]
Loading 0:  12%|█▏        | 43/363 [00:01<00:11, 27.14it/s]
Loading 0:  13%|█▎        | 48/363 [00:01<00:10, 28.86it/s]
Loading 0:  14%|█▍        | 52/363 [00:01<00:11, 28.18it/s]
Loading 0:  15%|█▌        | 56/363 [00:02<00:10, 28.93it/s]
Loading 0:  17%|█▋        | 60/363 [00:02<00:09, 31.23it/s]
Loading 0:  18%|█▊        | 64/363 [00:02<00:14, 20.28it/s]
Loading 0:  20%|█▉        | 71/363 [00:02<00:10, 26.85it/s]
Loading 0:  21%|██        | 75/363 [00:02<00:10, 26.60it/s]
Loading 0:  22%|██▏       | 79/363 [00:03<00:10, 26.29it/s]
Loading 0:  23%|██▎       | 82/363 [00:03<00:10, 26.86it/s]
Loading 0:  24%|██▎       | 86/363 [00:03<00:11, 24.51it/s]
Loading 0:  25%|██▌       | 92/363 [00:03<00:08, 31.84it/s]
Loading 0:  26%|██▋       | 96/363 [00:03<00:09, 26.91it/s]
Loading 0:  28%|██▊       | 100/363 [00:03<00:08, 29.30it/s]
Loading 0:  29%|██▊       | 104/363 [00:04<00:13, 19.28it/s]
Loading 0:  30%|███       | 109/363 [00:04<00:10, 23.96it/s]
Loading 0:  31%|███       | 113/363 [00:04<00:11, 22.41it/s]
Loading 0:  33%|███▎      | 120/363 [00:04<00:08, 28.21it/s]
Loading 0:  34%|███▍      | 124/363 [00:04<00:08, 27.06it/s]
Loading 0:  36%|███▌      | 129/363 [00:04<00:07, 29.71it/s]
Loading 0:  37%|███▋      | 133/363 [00:05<00:08, 28.12it/s]
Loading 0:  38%|███▊      | 137/363 [00:05<00:07, 28.41it/s]
Loading 0:  39%|███▉      | 142/363 [00:05<00:09, 24.24it/s]
Loading 0:  40%|███▉      | 145/363 [00:05<00:09, 22.68it/s]
Loading 0:  41%|████      | 149/363 [00:05<00:10, 21.32it/s]
Loading 0:  42%|████▏     | 154/363 [00:05<00:07, 26.39it/s]
Loading 0:  44%|████▎     | 158/363 [00:06<00:08, 23.61it/s]
Loading 0:  45%|████▍     | 163/363 [00:06<00:07, 28.18it/s]
Loading 0:  46%|████▌     | 167/363 [00:06<00:07, 25.18it/s]
Loading 0:  48%|████▊     | 174/363 [00:06<00:05, 31.75it/s]
Loading 0:  49%|████▉     | 178/363 [00:06<00:06, 29.40it/s]
Loading 0:  50%|█████     | 182/363 [00:07<00:07, 24.22it/s]
Loading 0:  51%|█████     | 185/363 [00:07<00:08, 21.40it/s]
Loading 0:  53%|█████▎    | 192/363 [00:07<00:06, 28.21it/s]
Loading 0:  54%|█████▍    | 196/363 [00:07<00:06, 27.54it/s]
Loading 0:  55%|█████▌    | 201/363 [00:07<00:05, 30.16it/s]
Loading 0:  56%|█████▋    | 205/363 [00:07<00:05, 29.19it/s]
Loading 0:  58%|█████▊    | 210/363 [00:07<00:04, 31.55it/s]
Loading 0:  59%|█████▉    | 214/363 [00:08<00:05, 29.46it/s]
Loading 0:  60%|██████    | 218/363 [00:08<00:04, 29.15it/s]
Loading 0:  61%|██████▏   | 223/363 [00:08<00:05, 25.76it/s]
Loading 0:  62%|██████▏   | 226/363 [00:08<00:05, 23.56it/s]
Loading 0:  63%|██████▎   | 230/363 [00:08<00:05, 22.46it/s]
Loading 0:  65%|██████▌   | 237/363 [00:08<00:04, 29.29it/s]
Loading 0:  66%|██████▋   | 241/363 [00:09<00:04, 28.05it/s]
Loading 0:  68%|██████▊   | 246/363 [00:09<00:03, 30.60it/s]
Loading 0:  69%|██████▉   | 250/363 [00:09<00:03, 28.96it/s]
Loading 0:  70%|███████   | 255/363 [00:09<00:03, 30.70it/s]
Loading 0:  71%|███████▏  | 259/363 [00:09<00:03, 28.56it/s]
Loading 0:  72%|███████▏  | 263/363 [00:09<00:04, 23.08it/s]
Loading 0:  73%|███████▎  | 266/363 [00:10<00:04, 20.46it/s]
Loading 0:  75%|███████▍  | 271/363 [00:10<00:03, 25.57it/s]
Loading 0:  76%|███████▌  | 275/363 [00:10<00:03, 23.60it/s]
Loading 0:  78%|███████▊  | 282/363 [00:10<00:02, 30.40it/s]
Loading 0:  79%|███████▉  | 286/363 [00:10<00:02, 28.68it/s]
Loading 0:  80%|███████▉  | 290/363 [00:10<00:02, 30.79it/s]
Loading 0:  81%|████████  | 294/363 [00:11<00:02, 26.63it/s]
Loading 0:  82%|████████▏ | 299/363 [00:11<00:02, 29.16it/s]
Loading 0:  84%|████████▎ | 304/363 [00:11<00:02, 24.55it/s]
Loading 0:  85%|████████▍ | 307/363 [00:11<00:02, 22.98it/s]
Loading 0:  86%|████████▌ | 311/363 [00:11<00:02, 21.85it/s]
Loading 0:  87%|████████▋ | 316/363 [00:12<00:01, 26.52it/s]
Loading 0:  88%|████████▊ | 320/363 [00:12<00:01, 24.22it/s]
Loading 0:  90%|█████████ | 327/363 [00:12<00:01, 30.64it/s]
Loading 0:  91%|█████████ | 331/363 [00:12<00:01, 29.71it/s]
Loading 0:  93%|█████████▎| 336/363 [00:12<00:00, 32.31it/s]
Loading 0:  94%|█████████▎| 340/363 [00:12<00:00, 30.60it/s]
Loading 0:  95%|█████████▍| 344/363 [00:13<00:01, 15.23it/s]
Loading 0:  96%|█████████▌| 348/363 [00:13<00:00, 16.35it/s]
Loading 0:  97%|█████████▋| 353/363 [00:13<00:00, 19.64it/s]
Loading 0:  98%|█████████▊| 357/363 [00:13<00:00, 20.25it/s]
                                                            

Job albertwang8192-2025-07-04-1-v1-mkmlizer completed after 248.84s with status: succeeded
Stopping job with name albertwang8192-2025-07-04-1-v1-mkmlizer
Pipeline stage MKMLizer completed in 249.49s
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 albertwang8192-2025-07-04-1-v1
Waiting for inference service albertwang8192-2025-07-04-1-v1 to be ready
Inference service albertwang8192-2025-07-04-1-v1 ready after 220.92456126213074s
Pipeline stage MKMLDeployer completed in 221.53s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.3067080974578857s
Received healthy response to inference request in 1.5751256942749023s
Received healthy response to inference request in 2.003856658935547s
Received healthy response to inference request in 1.751401662826538s
Received healthy response to inference request in 1.7217738628387451s
5 requests
0 failed requests
5th percentile: 1.604455327987671
10th percentile: 1.6337849617004394
20th percentile: 1.6924442291259765
30th percentile: 1.7276994228363036
40th percentile: 1.7395505428314209
50th percentile: 1.751401662826538
60th percentile: 1.8523836612701416
70th percentile: 1.953365659713745
80th percentile: 2.064426946640015
90th percentile: 2.18556752204895
95th percentile: 2.2461378097534177
99th percentile: 2.294594039916992
mean time: 1.8717731952667236
Pipeline stage StressChecker completed in 10.79s
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 0.65s
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 0.79s
Shutdown handler de-registered
albertwang8192-2025-07-04-1_v1 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
Pipeline stage OfflineFamilyFriendlyScorer completed in 3018.10s
Shutdown handler de-registered
albertwang8192-2025-07-04-1_v1 status is now inactive due to auto deactivation removed underperforming models
albertwang8192-2025-07-04-1_v1 status is now torndown due to DeploymentManager action