albertwang8192-2025-07-08-0

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-08-0_v1

model_name: 2025-07-08_0

model_group: AlbertWang8192/2025-07-0

status: torndown

timestamp: 2025-07-08T05:17:40+00:00

num_battles: 5947

num_wins: 2662

celo_rating: 1250.91

family_friendly_score: 0.595

family_friendly_standard_error: 0.00694226187924368

submission_type: basic

model_repo: AlbertWang8192/2025-07-08_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': 0.598553939556994, 'latency_mean': 1.6705951964855195, 'latency_p50': 1.667898416519165, 'latency_p90': 1.854670786857605}, {'batch_size': 3, 'throughput': 1.0799220134481125, 'latency_mean': 2.764692311286926, 'latency_p50': 2.765515089035034, 'latency_p90': 3.105814790725708}, {'batch_size': 5, 'throughput': 1.2836341501219433, 'latency_mean': 3.8752297842502594, 'latency_p50': 3.8683440685272217, 'latency_p90': 4.333337950706482}, {'batch_size': 6, 'throughput': 1.3533113186663657, 'latency_mean': 4.409194235801697, 'latency_p50': 4.41704785823822, 'latency_p90': 4.987717318534851}, {'batch_size': 8, 'throughput': 1.4130568229401146, 'latency_mean': 5.621921122074127, 'latency_p50': 5.643206834793091, 'latency_p90': 6.279145669937134}, {'batch_size': 10, 'throughput': 1.4442132548883269, 'latency_mean': 6.87155718922615, 'latency_p50': 6.882639527320862, 'latency_p90': 7.801050519943237}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-08_0

is_internal_developer: False

language_model: AlbertWang8192/2025-07-08_0

model_size: 13B

ranking_group: single

throughput_3p7s: 1.27

us_pacific_date: 2025-07-07

win_ratio: 0.44762064906675636

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|>', '<|im_end|>', '\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
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Running pipeline stage MKMLizer
Starting job with name albertwang8192-2025-07-08-0-v1-mkmlizer
Waiting for job on albertwang8192-2025-07-08-0-v1-mkmlizer to finish
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albertwang8192-2025-07-08-0-v1-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-08-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-08-0-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-08-0-v1-mkmlizer: Downloaded to shared memory in 40.717s
albertwang8192-2025-07-08-0-v1-mkmlizer: Checking if AlbertWang8192/2025-07-08_0 already exists in ChaiML
albertwang8192-2025-07-08-0-v1-mkmlizer: Creating repo ChaiML/2025-07-08_0 and uploading /tmp/tmppi9mptu1 to it
albertwang8192-2025-07-08-0-v1-mkmlizer: 
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albertwang8192-2025-07-08-0-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmppi9mptu1, device:0
albertwang8192-2025-07-08-0-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-08-0-v1-mkmlizer: quantized model in 30.436s
albertwang8192-2025-07-08-0-v1-mkmlizer: Processed model AlbertWang8192/2025-07-08_0 in 125.836s
albertwang8192-2025-07-08-0-v1-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-08-0-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-08-0-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-08-0-v1/nvidia
albertwang8192-2025-07-08-0-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-08-0-v1/nvidia/config.json
albertwang8192-2025-07-08-0-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-08-0-v1/nvidia/special_tokens_map.json
albertwang8192-2025-07-08-0-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-08-0-v1/nvidia/flywheel_model.0.safetensors
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Job albertwang8192-2025-07-08-0-v1-mkmlizer completed after 146.73s with status: succeeded
Stopping job with name albertwang8192-2025-07-08-0-v1-mkmlizer
Pipeline stage MKMLizer completed in 147.33s
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Running pipeline stage MKMLDeployer
Creating inference service albertwang8192-2025-07-08-0-v1
Waiting for inference service albertwang8192-2025-07-08-0-v1 to be ready
Inference service albertwang8192-2025-07-08-0-v1 ready after 171.06587600708008s
Pipeline stage MKMLDeployer completed in 171.62s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.493833065032959s
Received healthy response to inference request in 1.5171914100646973s
Received healthy response to inference request in 1.251335620880127s
Received healthy response to inference request in 1.359250545501709s
Received healthy response to inference request in 1.9902303218841553s
5 requests
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5th percentile: 1.2729186058044433
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