albertwang8192-2025-07-11-7

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-11-7_v6

model_name: 2025-07-11_7_v6

model_group: AlbertWang8192/2025-07-1

status: torndown

timestamp: 2025-07-12T14:33:56+00:00

num_battles: 10257

num_wins: 4862

celo_rating: 1268.54

family_friendly_score: 0.5464

family_friendly_standard_error: 0.007040554523615309

submission_type: basic

model_repo: AlbertWang8192/2025-07-11_7

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': 0.5915216523542153, 'latency_mean': 1.6903706550598145, 'latency_p50': 1.7076414823532104, 'latency_p90': 1.8528423070907594}, {'batch_size': 3, 'throughput': 1.0820586242308083, 'latency_mean': 2.7656577050685884, 'latency_p50': 2.7670024633407593, 'latency_p90': 3.023830008506775}, {'batch_size': 5, 'throughput': 1.2845337518417053, 'latency_mean': 3.8688828420639036, 'latency_p50': 3.869574785232544, 'latency_p90': 4.337608456611633}, {'batch_size': 6, 'throughput': 1.360783139407186, 'latency_mean': 4.384749863147736, 'latency_p50': 4.401211977005005, 'latency_p90': 4.887700939178466}, {'batch_size': 8, 'throughput': 1.4116465739337847, 'latency_mean': 5.619059680700302, 'latency_p50': 5.644812226295471, 'latency_p90': 6.3497631549835205}, {'batch_size': 10, 'throughput': 1.4463603517704475, 'latency_mean': 6.855705485343933, 'latency_p50': 6.835245370864868, 'latency_p90': 7.730505633354187}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-11_7_v6

is_internal_developer: False

language_model: AlbertWang8192/2025-07-11_7

model_size: 13B

ranking_group: single

throughput_3p7s: 1.27

us_pacific_date: 2025-07-12

win_ratio: 0.4740177439797212

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': ['<|im_start|>', '\n', '<|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': True}

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 albertwang8192-2025-07-11-7-v6-mkmlizer
Waiting for job on albertwang8192-2025-07-11-7-v6-mkmlizer to finish
albertwang8192-2025-07-11-7-v6-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
albertwang8192-2025-07-11-7-v6-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v6-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-11-7-v6-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`
albertwang8192-2025-07-11-7-v6-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`
albertwang8192-2025-07-11-7-v6-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`
albertwang8192-2025-07-11-7-v6-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`
albertwang8192-2025-07-11-7-v6-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`
albertwang8192-2025-07-11-7-v6-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`
albertwang8192-2025-07-11-7-v6-mkmlizer: Downloaded to shared memory in 30.790s
albertwang8192-2025-07-11-7-v6-mkmlizer: Checking if AlbertWang8192/2025-07-11_7 already exists in ChaiML
albertwang8192-2025-07-11-7-v6-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpwrxxmhir, device:0
albertwang8192-2025-07-11-7-v6-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-11-7-v6-mkmlizer: quantized model in 29.778s
albertwang8192-2025-07-11-7-v6-mkmlizer: Processed model AlbertWang8192/2025-07-11_7 in 60.664s
albertwang8192-2025-07-11-7-v6-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-11-7-v6-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-11-7-v6-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v6/nvidia
albertwang8192-2025-07-11-7-v6-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v6/nvidia/config.json
albertwang8192-2025-07-11-7-v6-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v6/nvidia/special_tokens_map.json
albertwang8192-2025-07-11-7-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v6/nvidia/tokenizer_config.json
albertwang8192-2025-07-11-7-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v6/nvidia/tokenizer.json
albertwang8192-2025-07-11-7-v6-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v6/nvidia/flywheel_model.0.safetensors
albertwang8192-2025-07-11-7-v6-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:11, 30.82it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:06, 51.17it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:07, 47.56it/s]
Loading 0:   7%|▋         | 24/363 [00:00<00:07, 45.71it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:06, 51.81it/s]
Loading 0:  10%|█         | 37/363 [00:00<00:06, 48.62it/s]
Loading 0:  12%|█▏        | 42/363 [00:00<00:06, 46.57it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:06, 51.43it/s]
Loading 0:  15%|█▌        | 55/363 [00:01<00:06, 48.69it/s]
Loading 0:  17%|█▋        | 61/363 [00:01<00:08, 36.05it/s]
Loading 0:  18%|█▊        | 66/363 [00:01<00:08, 35.76it/s]
Loading 0:  20%|█▉        | 71/363 [00:01<00:07, 37.95it/s]
Loading 0:  21%|██        | 76/363 [00:01<00:07, 38.10it/s]
Loading 0:  22%|██▏       | 81/363 [00:01<00:07, 38.70it/s]
Loading 0:  24%|██▎       | 86/363 [00:02<00:06, 40.94it/s]
Loading 0:  25%|██▌       | 91/363 [00:02<00:07, 35.95it/s]
Loading 0:  27%|██▋       | 98/363 [00:02<00:06, 43.82it/s]
Loading 0:  28%|██▊       | 103/363 [00:02<00:05, 43.72it/s]
Loading 0:  30%|███       | 109/363 [00:02<00:05, 47.80it/s]
Loading 0:  32%|███▏      | 115/363 [00:02<00:06, 41.09it/s]
Loading 0:  33%|███▎      | 120/363 [00:02<00:06, 39.76it/s]
Loading 0:  35%|███▍      | 126/363 [00:02<00:05, 42.68it/s]
Loading 0:  36%|███▌      | 131/363 [00:03<00:05, 44.16it/s]
Loading 0:  37%|███▋      | 136/363 [00:03<00:06, 37.34it/s]
Loading 0:  39%|███▉      | 142/363 [00:03<00:06, 31.78it/s]
Loading 0:  40%|████      | 146/363 [00:03<00:06, 32.20it/s]
Loading 0:  41%|████▏     | 150/363 [00:03<00:06, 32.07it/s]
Loading 0:  43%|████▎     | 156/363 [00:03<00:05, 38.03it/s]
Loading 0:  44%|████▍     | 161/363 [00:03<00:05, 40.23it/s]
Loading 0:  46%|████▌     | 166/363 [00:04<00:04, 41.54it/s]
Loading 0:  47%|████▋     | 171/363 [00:04<00:04, 43.58it/s]
Loading 0:  48%|████▊     | 176/363 [00:04<00:05, 35.69it/s]
Loading 0:  50%|█████     | 183/363 [00:04<00:04, 43.40it/s]
Loading 0:  52%|█████▏    | 188/363 [00:04<00:04, 43.10it/s]
Loading 0:  53%|█████▎    | 193/363 [00:04<00:03, 43.48it/s]
Loading 0:  55%|█████▍    | 199/363 [00:04<00:03, 42.25it/s]
Loading 0:  56%|█████▌    | 204/363 [00:04<00:03, 41.36it/s]
Loading 0:  58%|█████▊    | 210/363 [00:05<00:03, 45.83it/s]
Loading 0:  59%|█████▉    | 215/363 [00:05<00:03, 45.19it/s]
Loading 0:  61%|██████    | 222/363 [00:05<00:03, 44.99it/s]
Loading 0:  63%|██████▎   | 227/363 [00:05<00:04, 31.42it/s]
Loading 0:  64%|██████▎   | 231/363 [00:05<00:04, 31.31it/s]
Loading 0:  65%|██████▌   | 237/363 [00:05<00:03, 36.94it/s]
Loading 0:  67%|██████▋   | 242/363 [00:05<00:03, 38.56it/s]
Loading 0:  68%|██████▊   | 247/363 [00:06<00:02, 40.43it/s]
Loading 0:  69%|██████▉   | 252/363 [00:06<00:02, 42.77it/s]
Loading 0:  71%|███████   | 257/363 [00:06<00:02, 35.71it/s]
Loading 0:  73%|███████▎  | 265/363 [00:06<00:02, 43.70it/s]
Loading 0:  74%|███████▍  | 270/363 [00:06<00:02, 45.08it/s]
Loading 0:  76%|███████▌  | 275/363 [00:06<00:02, 37.72it/s]
Loading 0:  78%|███████▊  | 282/363 [00:06<00:01, 44.31it/s]
Loading 0:  79%|███████▉  | 287/363 [00:07<00:01, 41.89it/s]
Loading 0:  80%|████████  | 292/363 [00:07<00:01, 41.44it/s]
Loading 0:  82%|████████▏ | 297/363 [00:07<00:01, 42.51it/s]
Loading 0:  83%|████████▎ | 303/363 [00:07<00:01, 42.04it/s]
Loading 0:  85%|████████▍ | 308/363 [00:07<00:02, 22.79it/s]
Loading 0:  86%|████████▌ | 312/363 [00:08<00:02, 23.66it/s]
Loading 0:  88%|████████▊ | 320/363 [00:08<00:01, 32.55it/s]
Loading 0:  90%|████████▉ | 326/363 [00:08<00:01, 34.78it/s]
Loading 0:  91%|█████████ | 331/363 [00:08<00:00, 36.51it/s]
Loading 0:  93%|█████████▎| 338/363 [00:08<00:00, 42.34it/s]
Loading 0:  94%|█████████▍| 343/363 [00:08<00:00, 44.05it/s]
Loading 0:  96%|█████████▌| 348/363 [00:08<00:00, 38.67it/s]
Loading 0:  98%|█████████▊| 356/363 [00:08<00:00, 46.87it/s]
Loading 0: 100%|█████████▉| 362/363 [00:09<00:00, 44.99it/s]
                                                            
Job albertwang8192-2025-07-11-7-v6-mkmlizer completed after 84.95s with status: succeeded
Stopping job with name albertwang8192-2025-07-11-7-v6-mkmlizer
Pipeline stage MKMLizer completed in 85.64s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.45s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service albertwang8192-2025-07-11-7-v6
Waiting for inference service albertwang8192-2025-07-11-7-v6 to be ready
Inference service albertwang8192-2025-07-11-7-v6 ready after 200.77909636497498s
Pipeline stage MKMLDeployer completed in 201.34s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.507829427719116s
Received healthy response to inference request in 1.6154603958129883s
Received healthy response to inference request in 1.9736576080322266s
Received healthy response to inference request in 1.917217493057251s
Received healthy response to inference request in 1.840851068496704s
5 requests
0 failed requests
5th percentile: 1.6605385303497315
10th percentile: 1.7056166648864746
20th percentile: 1.7957729339599608
30th percentile: 1.8561243534088134
40th percentile: 1.8866709232330323
50th percentile: 1.917217493057251
60th percentile: 1.9397935390472412
70th percentile: 1.9623695850372314
80th percentile: 2.0804919719696047
90th percentile: 2.2941606998443604
95th percentile: 2.400995063781738
99th percentile: 2.4864625549316406
mean time: 1.9710031986236571
Pipeline stage StressChecker completed in 11.17s
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 0.73s
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 0.71s
Shutdown handler de-registered
albertwang8192-2025-07-11-7_v6 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 6012.94s
Shutdown handler de-registered
albertwang8192-2025-07-11-7_v6 status is now inactive due to auto deactivation removed underperforming models
albertwang8192-2025-07-11-7_v6 status is now torndown due to DeploymentManager action