albertwang8192-2025-07-08-9

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-08-9_v1

model_name: 2025-07-08_9

model_group: AlbertWang8192/2025-07-0

status: torndown

timestamp: 2025-07-08T23:26:29+00:00

num_battles: 6495

num_wins: 3062

celo_rating: 1257.9

family_friendly_score: 0.595

family_friendly_standard_error: 0.00694226187924368

submission_type: basic

model_repo: AlbertWang8192/2025-07-08_9

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': 0.594019958781076, 'latency_mean': 1.6833406281471253, 'latency_p50': 1.69096040725708, 'latency_p90': 1.829724955558777}, {'batch_size': 3, 'throughput': 1.0649854732252901, 'latency_mean': 2.8082813251018526, 'latency_p50': 2.808740496635437, 'latency_p90': 3.1150297641754148}, {'batch_size': 5, 'throughput': 1.2660887302981676, 'latency_mean': 3.923310704231262, 'latency_p50': 3.92838716506958, 'latency_p90': 4.396691751480103}, {'batch_size': 6, 'throughput': 1.3364670268307457, 'latency_mean': 4.464489308595657, 'latency_p50': 4.484921336174011, 'latency_p90': 4.923110365867615}, {'batch_size': 8, 'throughput': 1.394687948478947, 'latency_mean': 5.69575010061264, 'latency_p50': 5.670409202575684, 'latency_p90': 6.356204724311828}, {'batch_size': 10, 'throughput': 1.4273996265837248, 'latency_mean': 6.947895138263703, 'latency_p50': 6.960236191749573, 'latency_p90': 7.785775542259216}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-08_9

is_internal_developer: False

language_model: AlbertWang8192/2025-07-08_9

model_size: 13B

ranking_group: single

throughput_3p7s: 1.24

us_pacific_date: 2025-07-08

win_ratio: 0.47143956889915317

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_start|>', '<|im_end|>'], '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 albertwang8192-2025-07-08-9-v1-mkmlizer
Waiting for job on albertwang8192-2025-07-08-9-v1-mkmlizer to finish
albertwang8192-2025-07-08-9-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
albertwang8192-2025-07-08-9-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-9-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-08-9-v1-mkmlizer: Downloaded to shared memory in 42.720s
albertwang8192-2025-07-08-9-v1-mkmlizer: Checking if AlbertWang8192/2025-07-08_9 already exists in ChaiML
albertwang8192-2025-07-08-9-v1-mkmlizer: Creating repo ChaiML/2025-07-08_9 and uploading /tmp/tmpe_0vnx1r to it
albertwang8192-2025-07-08-9-v1-mkmlizer: 
  0%|          | 0/6 [00:00<?, ?it/s]
 17%|█▋        | 1/6 [00:06<00:34,  6.85s/it]
 33%|███▎      | 2/6 [00:15<00:30,  7.65s/it]
 50%|█████     | 3/6 [00:18<00:17,  5.83s/it]
 67%|██████▋   | 4/6 [00:22<00:10,  5.05s/it]
 83%|████████▎ | 5/6 [00:30<00:06,  6.05s/it]
100%|██████████| 6/6 [00:31<00:00,  4.36s/it]
100%|██████████| 6/6 [00:31<00:00,  5.25s/it]
albertwang8192-2025-07-08-9-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpe_0vnx1r, device:0
albertwang8192-2025-07-08-9-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-08-9-v1-mkmlizer: quantized model in 31.577s
albertwang8192-2025-07-08-9-v1-mkmlizer: Processed model AlbertWang8192/2025-07-08_9 in 133.339s
albertwang8192-2025-07-08-9-v1-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-08-9-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-08-9-v1/nvidia/special_tokens_map.json
albertwang8192-2025-07-08-9-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-08-9-v1/nvidia/config.json
albertwang8192-2025-07-08-9-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-08-9-v1/nvidia/tokenizer_config.json
albertwang8192-2025-07-08-9-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-08-9-v1/nvidia/tokenizer.json
albertwang8192-2025-07-08-9-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-08-9-v1/nvidia/flywheel_model.0.safetensors
albertwang8192-2025-07-08-9-v1-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:12, 28.77it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:07, 47.75it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:08, 42.18it/s]
Loading 0:   7%|▋         | 24/363 [00:00<00:08, 40.33it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:07, 45.77it/s]
Loading 0:  10%|▉         | 36/363 [00:00<00:07, 45.58it/s]
Loading 0:  11%|█▏        | 41/363 [00:01<00:08, 38.11it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:06, 46.73it/s]
Loading 0:  15%|█▌        | 55/363 [00:01<00:06, 45.56it/s]
Loading 0:  17%|█▋        | 61/363 [00:01<00:09, 32.15it/s]
Loading 0:  18%|█▊        | 65/363 [00:01<00:09, 31.51it/s]
Loading 0:  20%|█▉        | 72/363 [00:01<00:07, 38.03it/s]
Loading 0:  21%|██        | 77/363 [00:01<00:07, 40.37it/s]
Loading 0:  23%|██▎       | 82/363 [00:02<00:08, 35.00it/s]
Loading 0:  25%|██▍       | 90/363 [00:02<00:06, 42.73it/s]
Loading 0:  26%|██▌       | 95/363 [00:02<00:06, 43.50it/s]
Loading 0:  28%|██▊       | 100/363 [00:02<00:07, 36.76it/s]
Loading 0:  30%|██▉       | 108/363 [00:02<00:05, 45.67it/s]
Loading 0:  31%|███▏      | 114/363 [00:02<00:05, 42.24it/s]
Loading 0:  33%|███▎      | 119/363 [00:02<00:06, 39.42it/s]
Loading 0:  34%|███▍      | 125/363 [00:03<00:05, 43.64it/s]
Loading 0:  36%|███▌      | 130/363 [00:03<00:05, 41.74it/s]
Loading 0:  37%|███▋      | 135/363 [00:03<00:05, 40.79it/s]
Loading 0:  39%|███▊      | 140/363 [00:03<00:05, 41.51it/s]
Loading 0:  40%|███▉      | 145/363 [00:03<00:08, 25.17it/s]
Loading 0:  41%|████      | 149/363 [00:03<00:08, 25.63it/s]
Loading 0:  43%|████▎     | 156/363 [00:04<00:06, 33.13it/s]
Loading 0:  44%|████▍     | 161/363 [00:04<00:05, 34.62it/s]
Loading 0:  46%|████▌     | 166/363 [00:04<00:05, 36.27it/s]
Loading 0:  47%|████▋     | 171/363 [00:04<00:04, 39.19it/s]
Loading 0:  48%|████▊     | 176/363 [00:04<00:05, 33.86it/s]
Loading 0:  50%|█████     | 183/363 [00:04<00:04, 40.85it/s]
Loading 0:  52%|█████▏    | 188/363 [00:04<00:04, 40.00it/s]
Loading 0:  53%|█████▎    | 193/363 [00:05<00:04, 40.27it/s]
Loading 0:  55%|█████▍    | 198/363 [00:05<00:03, 42.63it/s]
Loading 0:  56%|█████▌    | 203/363 [00:05<00:04, 35.84it/s]
Loading 0:  58%|█████▊    | 210/363 [00:05<00:03, 43.14it/s]
Loading 0:  59%|█████▉    | 215/363 [00:05<00:03, 42.45it/s]
Loading 0:  61%|██████    | 220/363 [00:05<00:03, 43.51it/s]
Loading 0:  62%|██████▏   | 225/363 [00:06<00:05, 25.56it/s]
Loading 0:  63%|██████▎   | 230/363 [00:06<00:04, 27.48it/s]
Loading 0:  65%|██████▌   | 237/363 [00:06<00:03, 34.74it/s]
Loading 0:  67%|██████▋   | 242/363 [00:06<00:03, 35.57it/s]
Loading 0:  68%|██████▊   | 247/363 [00:06<00:03, 36.88it/s]
Loading 0:  69%|██████▉   | 252/363 [00:06<00:02, 39.12it/s]
Loading 0:  71%|███████   | 257/363 [00:06<00:03, 32.82it/s]
Loading 0:  73%|███████▎  | 264/363 [00:07<00:02, 38.87it/s]
Loading 0:  74%|███████▍  | 269/363 [00:07<00:02, 38.65it/s]
Loading 0:  75%|███████▌  | 274/363 [00:07<00:02, 39.02it/s]
Loading 0:  77%|███████▋  | 279/363 [00:07<00:02, 40.90it/s]
Loading 0:  78%|███████▊  | 284/363 [00:07<00:02, 34.30it/s]
Loading 0:  80%|████████  | 291/363 [00:07<00:01, 40.84it/s]
Loading 0:  82%|████████▏ | 296/363 [00:07<00:01, 40.82it/s]
Loading 0:  83%|████████▎ | 301/363 [00:07<00:01, 42.15it/s]
Loading 0:  84%|████████▍ | 306/363 [00:08<00:02, 21.52it/s]
Loading 0:  85%|████████▌ | 310/363 [00:08<00:02, 22.47it/s]
Loading 0:  87%|████████▋ | 314/363 [00:08<00:01, 25.13it/s]
Loading 0:  88%|████████▊ | 320/363 [00:08<00:01, 30.83it/s]
Loading 0:  90%|████████▉ | 325/363 [00:08<00:01, 34.46it/s]
Loading 0:  91%|█████████ | 330/363 [00:09<00:01, 30.77it/s]
Loading 0:  93%|█████████▎| 337/363 [00:09<00:00, 38.42it/s]
Loading 0:  94%|█████████▍| 342/363 [00:09<00:00, 39.46it/s]
Loading 0:  96%|█████████▌| 347/363 [00:09<00:00, 39.16it/s]
Loading 0:  97%|█████████▋| 352/363 [00:09<00:00, 41.11it/s]
Loading 0:  98%|█████████▊| 357/363 [00:09<00:00, 35.65it/s]
                                                            
Job albertwang8192-2025-07-08-9-v1-mkmlizer completed after 166.95s with status: succeeded
Stopping job with name albertwang8192-2025-07-08-9-v1-mkmlizer
Pipeline stage MKMLizer completed in 167.44s
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 albertwang8192-2025-07-08-9-v1
Waiting for inference service albertwang8192-2025-07-08-9-v1 to be ready
Inference service albertwang8192-2025-07-08-9-v1 ready after 191.080632686615s
Pipeline stage MKMLDeployer completed in 191.63s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.7072479724884033s
Received healthy response to inference request in 1.5788524150848389s
Received healthy response to inference request in 1.5003807544708252s
Received healthy response to inference request in 1.454416036605835s
Received healthy response to inference request in 2.026644706726074s
5 requests
0 failed requests
5th percentile: 1.463608980178833
10th percentile: 1.472801923751831
20th percentile: 1.4911878108978271
30th percentile: 1.5160750865936279
40th percentile: 1.5474637508392335
50th percentile: 1.5788524150848389
60th percentile: 1.757969331741333
70th percentile: 1.937086248397827
80th percentile: 2.16276535987854
90th percentile: 2.4350066661834715
95th percentile: 2.5711273193359374
99th percentile: 2.6800238418579103
mean time: 1.8535083770751952
Pipeline stage StressChecker completed in 10.65s
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 0.72s
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
albertwang8192-2025-07-08-9_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 3041.60s
Shutdown handler de-registered
albertwang8192-2025-07-08-9_v1 status is now inactive due to auto deactivation removed underperforming models
albertwang8192-2025-07-08-9_v1 status is now torndown due to DeploymentManager action