albertwang8192-2025-07-13-0

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-13-0_v1

model_name: 2025-07-13_0

model_group: AlbertWang8192/2025-07-1

status: torndown

timestamp: 2025-07-13T16:00:08+00:00

num_battles: 7938

num_wins: 3626

celo_rating: 1265.65

family_friendly_score: 0.0

family_friendly_standard_error: 0.0

submission_type: basic

model_repo: AlbertWang8192/2025-07-13_0

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': 0.5939141908928192, 'latency_mean': 1.6836203408241273, 'latency_p50': 1.677638292312622, 'latency_p90': 1.866228175163269}, {'batch_size': 3, 'throughput': 1.0669030376650002, 'latency_mean': 2.806346629858017, 'latency_p50': 2.833011746406555, 'latency_p90': 3.1192368268966675}, {'batch_size': 5, 'throughput': 1.2986169750146028, 'latency_mean': 3.8370222842693327, 'latency_p50': 3.8148770332336426, 'latency_p90': 4.301986241340638}, {'batch_size': 6, 'throughput': 1.344155739607154, 'latency_mean': 4.43175134062767, 'latency_p50': 4.41680121421814, 'latency_p90': 5.023208093643189}, {'batch_size': 8, 'throughput': 1.401526463123748, 'latency_mean': 5.6636977541446685, 'latency_p50': 5.657292008399963, 'latency_p90': 6.235001969337463}, {'batch_size': 10, 'throughput': 1.4503771412675048, 'latency_mean': 6.849659847021103, 'latency_p50': 6.8536823987960815, 'latency_p90': 7.702241921424866}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-13_0

is_internal_developer: False

language_model: AlbertWang8192/2025-07-13_0

model_size: 13B

ranking_group: single

throughput_3p7s: 1.28

us_pacific_date: 2025-07-13

win_ratio: 0.4567901234567901

generation_params: {'temperature': 0.6, 'top_p': 0.98, 'min_p': 0.05, 'top_k': 40, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['<|im_end|>', '\n', '<|im_start|>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}

formatter: {'memory_template': '<|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{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 albertwang8192-2025-07-13-0-v1-mkmlizer
Waiting for job on albertwang8192-2025-07-13-0-v1-mkmlizer to finish
albertwang8192-2025-07-13-0-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
albertwang8192-2025-07-13-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-13-0-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-13-0-v1-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`
albertwang8192-2025-07-13-0-v1-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`
albertwang8192-2025-07-13-0-v1-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`
albertwang8192-2025-07-13-0-v1-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`
albertwang8192-2025-07-13-0-v1-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`
albertwang8192-2025-07-13-0-v1-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`
albertwang8192-2025-07-13-0-v1-mkmlizer: Downloaded to shared memory in 54.024s
albertwang8192-2025-07-13-0-v1-mkmlizer: Checking if AlbertWang8192/2025-07-13_0 already exists in ChaiML
albertwang8192-2025-07-13-0-v1-mkmlizer: Creating repo ChaiML/2025-07-13_0 and uploading /tmp/tmpo0fr7957 to it
albertwang8192-2025-07-13-0-v1-mkmlizer: 
  0%|          | 0/6 [00:00<?, ?it/s]
 17%|█▋        | 1/6 [00:06<00:30,  6.02s/it]
 33%|███▎      | 2/6 [00:10<00:20,  5.17s/it]
 50%|█████     | 3/6 [00:17<00:17,  5.95s/it]
 67%|██████▋   | 4/6 [00:22<00:11,  5.54s/it]
 83%|████████▎ | 5/6 [00:29<00:06,  6.18s/it]
100%|██████████| 6/6 [00:30<00:00,  4.48s/it]
100%|██████████| 6/6 [00:30<00:00,  5.15s/it]
albertwang8192-2025-07-13-0-v1-mkmlizer: quantized model in 37.947s
albertwang8192-2025-07-13-0-v1-mkmlizer: Processed model AlbertWang8192/2025-07-13_0 in 155.038s
albertwang8192-2025-07-13-0-v1-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-13-0-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-13-0-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-13-0-v1/nvidia
albertwang8192-2025-07-13-0-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-13-0-v1/nvidia/config.json
albertwang8192-2025-07-13-0-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-13-0-v1/nvidia/special_tokens_map.json
albertwang8192-2025-07-13-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-13-0-v1/nvidia/tokenizer_config.json
albertwang8192-2025-07-13-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-13-0-v1/nvidia/tokenizer.json
albertwang8192-2025-07-13-0-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-13-0-v1/nvidia/flywheel_model.0.safetensors
albertwang8192-2025-07-13-0-v1-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:13, 26.01it/s]
Loading 0:   3%|▎         | 12/363 [00:00<00:08, 40.37it/s]
Loading 0:   5%|▍         | 17/363 [00:00<00:09, 37.57it/s]
Loading 0:   6%|▌         | 21/363 [00:00<00:09, 37.03it/s]
Loading 0:   7%|▋         | 25/363 [00:00<00:10, 33.71it/s]
Loading 0:   8%|▊         | 29/363 [00:00<00:09, 35.36it/s]
Loading 0:   9%|▉         | 33/363 [00:00<00:10, 30.79it/s]
Loading 0:  10%|█         | 37/363 [00:01<00:09, 32.96it/s]
Loading 0:  11%|█▏        | 41/363 [00:01<00:10, 30.07it/s]
Loading 0:  13%|█▎        | 48/363 [00:01<00:08, 37.92it/s]
Loading 0:  14%|█▍        | 52/363 [00:01<00:08, 34.88it/s]
Loading 0:  15%|█▌        | 56/363 [00:01<00:08, 34.75it/s]
Loading 0:  17%|█▋        | 61/363 [00:01<00:12, 24.98it/s]
Loading 0:  18%|█▊        | 64/363 [00:02<00:12, 23.84it/s]
Loading 0:  20%|█▉        | 71/363 [00:02<00:09, 32.27it/s]
Loading 0:  21%|██        | 75/363 [00:02<00:08, 32.41it/s]
Loading 0:  22%|██▏       | 80/363 [00:02<00:07, 35.38it/s]
Loading 0:  23%|██▎       | 84/363 [00:02<00:08, 34.02it/s]
Loading 0:  25%|██▍       | 89/363 [00:02<00:07, 36.62it/s]
Loading 0:  26%|██▌       | 93/363 [00:02<00:07, 34.92it/s]
Loading 0:  27%|██▋       | 98/363 [00:02<00:07, 37.30it/s]
Loading 0:  28%|██▊       | 102/363 [00:03<00:07, 35.50it/s]
Loading 0:  29%|██▉       | 106/363 [00:03<00:07, 34.78it/s]
Loading 0:  31%|███       | 112/363 [00:03<00:06, 38.30it/s]
Loading 0:  32%|███▏      | 116/363 [00:03<00:06, 36.26it/s]
Loading 0:  33%|███▎      | 120/363 [00:03<00:06, 34.79it/s]
Loading 0:  34%|███▍      | 125/363 [00:03<00:06, 36.69it/s]
Loading 0:  36%|███▌      | 129/363 [00:03<00:06, 34.68it/s]
Loading 0:  37%|███▋      | 134/363 [00:03<00:06, 36.29it/s]
Loading 0:  38%|███▊      | 138/363 [00:04<00:06, 34.14it/s]
Loading 0:  39%|███▉      | 142/363 [00:04<00:09, 23.33it/s]
Loading 0:  40%|███▉      | 145/363 [00:04<00:09, 23.26it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:08, 24.17it/s]
Loading 0:  42%|████▏     | 154/363 [00:04<00:07, 28.54it/s]
Loading 0:  44%|████▎     | 158/363 [00:04<00:07, 28.29it/s]
Loading 0:  45%|████▌     | 165/363 [00:05<00:05, 35.55it/s]
Loading 0:  47%|████▋     | 169/363 [00:05<00:05, 33.92it/s]
Loading 0:  48%|████▊     | 174/363 [00:05<00:05, 35.49it/s]
Loading 0:  49%|████▉     | 178/363 [00:05<00:05, 33.93it/s]
Loading 0:  50%|█████     | 183/363 [00:05<00:05, 35.14it/s]
Loading 0:  52%|█████▏    | 187/363 [00:05<00:05, 32.62it/s]
Loading 0:  53%|█████▎    | 192/363 [00:05<00:04, 34.61it/s]
Loading 0:  54%|█████▍    | 196/363 [00:05<00:04, 34.76it/s]
Loading 0:  55%|█████▌    | 201/363 [00:06<00:04, 36.88it/s]
Loading 0:  56%|█████▋    | 205/363 [00:06<00:04, 34.85it/s]
Loading 0:  58%|█████▊    | 210/363 [00:06<00:04, 37.87it/s]
Loading 0:  59%|█████▉    | 214/363 [00:06<00:04, 36.83it/s]
Loading 0:  60%|██████    | 218/363 [00:06<00:03, 36.98it/s]
Loading 0:  61%|██████▏   | 223/363 [00:06<00:04, 28.76it/s]
Loading 0:  63%|██████▎   | 227/363 [00:06<00:04, 29.15it/s]
Loading 0:  64%|██████▎   | 231/363 [00:07<00:04, 27.98it/s]
Loading 0:  65%|██████▍   | 235/363 [00:07<00:04, 30.61it/s]
Loading 0:  66%|██████▌   | 239/363 [00:07<00:04, 28.63it/s]
Loading 0:  67%|██████▋   | 244/363 [00:07<00:03, 33.44it/s]
Loading 0:  68%|██████▊   | 248/363 [00:07<00:03, 30.69it/s]
Loading 0:  70%|███████   | 255/363 [00:07<00:02, 37.64it/s]
Loading 0:  71%|███████▏  | 259/363 [00:07<00:02, 35.33it/s]
Loading 0:  73%|███████▎  | 264/363 [00:07<00:02, 36.75it/s]
Loading 0:  74%|███████▍  | 268/363 [00:08<00:02, 35.59it/s]
Loading 0:  75%|███████▌  | 273/363 [00:08<00:02, 37.05it/s]
Loading 0:  76%|███████▋  | 277/363 [00:08<00:02, 34.97it/s]
Loading 0:  78%|███████▊  | 282/363 [00:08<00:02, 36.78it/s]
Loading 0:  79%|███████▉  | 286/363 [00:08<00:02, 34.29it/s]
Loading 0:  80%|███████▉  | 290/363 [00:08<00:02, 35.63it/s]
Loading 0:  81%|████████  | 294/363 [00:08<00:02, 31.58it/s]
Loading 0:  82%|████████▏ | 298/363 [00:08<00:01, 33.56it/s]
Loading 0:  83%|████████▎ | 303/363 [00:09<00:01, 35.71it/s]
Loading 0:  85%|████████▍ | 307/363 [00:09<00:03, 18.09it/s]
Loading 0:  86%|████████▌ | 312/363 [00:09<00:02, 21.09it/s]
Loading 0:  88%|████████▊ | 319/363 [00:09<00:01, 28.90it/s]
Loading 0:  89%|████████▉ | 323/363 [00:09<00:01, 30.21it/s]
Loading 0:  90%|█████████ | 328/363 [00:10<00:01, 33.30it/s]
Loading 0:  91%|█████████▏| 332/363 [00:10<00:00, 32.27it/s]
Loading 0:  93%|█████████▎| 337/363 [00:10<00:00, 36.27it/s]
Loading 0:  94%|█████████▍| 342/363 [00:10<00:00, 36.48it/s]
Loading 0:  95%|█████████▌| 346/363 [00:10<00:00, 35.84it/s]
Loading 0:  96%|█████████▋| 350/363 [00:10<00:00, 34.27it/s]
Loading 0:  98%|█████████▊| 355/363 [00:10<00:00, 36.87it/s]
Loading 0:  99%|█████████▉| 359/363 [00:10<00:00, 34.89it/s]
                                                            
Job albertwang8192-2025-07-13-0-v1-mkmlizer completed after 188.48s with status: succeeded
Stopping job with name albertwang8192-2025-07-13-0-v1-mkmlizer
Pipeline stage MKMLizer completed in 189.02s
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 albertwang8192-2025-07-13-0-v1
Waiting for inference service albertwang8192-2025-07-13-0-v1 to be ready
Failed to get response for submission blend_fader_2025-07-10: ('http://chaiml-0sw-95p-5ff-rin-63828-v16-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:45548->127.0.0.1:8080: read: connection reset by peer\n')
Inference service albertwang8192-2025-07-13-0-v1 ready after 332.0599160194397s
Pipeline stage MKMLDeployer completed in 332.58s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.3863141536712646s
Received healthy response to inference request in 1.9157829284667969s
Received healthy response to inference request in 1.588804006576538s
Received healthy response to inference request in 1.7449655532836914s
Received healthy response to inference request in 1.6219792366027832s
5 requests
0 failed requests
5th percentile: 1.5954390525817872
10th percentile: 1.602074098587036
20th percentile: 1.615344190597534
30th percentile: 1.646576499938965
40th percentile: 1.6957710266113282
50th percentile: 1.7449655532836914
60th percentile: 1.8132925033569336
70th percentile: 1.8816194534301758
80th percentile: 2.0098891735076907
90th percentile: 2.1981016635894775
95th percentile: 2.292207908630371
99th percentile: 2.3674929046630857
mean time: 1.8515691757202148
Pipeline stage StressChecker completed in 10.51s
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 0.70s
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 0.75s
Shutdown handler de-registered
albertwang8192-2025-07-13-0_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
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
clean up pipeline due to error=DeploymentChecksError('None: None')
Shutdown handler de-registered
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
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
clean up pipeline due to error=DeploymentChecksError('None: None')
Shutdown handler de-registered
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
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
clean up pipeline due to error=DeploymentChecksError('None: None')
Shutdown handler de-registered
albertwang8192-2025-07-13-0_v1 status is now inactive due to auto deactivation removed underperforming models
albertwang8192-2025-07-13-0_v1 status is now torndown due to DeploymentManager action