albertwang8192-2025-07-11-2

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-11-2_v2

model_name: 2025-07-11_2_v2

model_group: AlbertWang8192/2025-07-1

status: torndown

timestamp: 2025-07-12T04:37:34+00:00

num_battles: 9372

num_wins: 4478

celo_rating: 1266.56

family_friendly_score: 0.5287999999999999

family_friendly_standard_error: 0.007059328013345179

submission_type: basic

model_repo: AlbertWang8192/2025-07-11_2

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': 0.5919805600674002, 'latency_mean': 1.6891148090362549, 'latency_p50': 1.6931545734405518, 'latency_p90': 1.8539365530014038}, {'batch_size': 3, 'throughput': 1.072776987944495, 'latency_mean': 2.793157540559769, 'latency_p50': 2.8151307106018066, 'latency_p90': 3.0610264062881467}, {'batch_size': 5, 'throughput': 1.2854973134532415, 'latency_mean': 3.8666970777511596, 'latency_p50': 3.829664707183838, 'latency_p90': 4.362566208839416}, {'batch_size': 6, 'throughput': 1.3529256159557488, 'latency_mean': 4.4156801068782805, 'latency_p50': 4.439074754714966, 'latency_p90': 5.041371893882751}, {'batch_size': 8, 'throughput': 1.4282353860975279, 'latency_mean': 5.566971204280853, 'latency_p50': 5.575278878211975, 'latency_p90': 6.24926061630249}, {'batch_size': 10, 'throughput': 1.4577932358003056, 'latency_mean': 6.811925077438355, 'latency_p50': 6.776750206947327, 'latency_p90': 7.673845481872558}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-11_2_v2

is_internal_developer: False

language_model: AlbertWang8192/2025-07-11_2

model_size: 13B

ranking_group: single

throughput_3p7s: 1.27

us_pacific_date: 2025-07-11

win_ratio: 0.4778062313273581

generation_params: {'temperature': 0.7, 'top_p': 0.95, 'min_p': 0.025, 'top_k': 60, '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': "{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 albertwang8192-2025-07-11-2-v2-mkmlizer
Waiting for job on albertwang8192-2025-07-11-2-v2-mkmlizer to finish
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albertwang8192-2025-07-11-2-v2-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-11-2-v2-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-11-2-v2-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`
albertwang8192-2025-07-11-2-v2-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`
albertwang8192-2025-07-11-2-v2-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`
albertwang8192-2025-07-11-2-v2-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`
albertwang8192-2025-07-11-2-v2-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`
albertwang8192-2025-07-11-2-v2-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`
albertwang8192-2025-07-11-2-v2-mkmlizer: Downloaded to shared memory in 32.153s
albertwang8192-2025-07-11-2-v2-mkmlizer: Checking if AlbertWang8192/2025-07-11_2 already exists in ChaiML
albertwang8192-2025-07-11-2-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp9fzyat93, device:0
albertwang8192-2025-07-11-2-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-11-2-v2-mkmlizer: quantized model in 30.547s
albertwang8192-2025-07-11-2-v2-mkmlizer: Processed model AlbertWang8192/2025-07-11_2 in 62.825s
albertwang8192-2025-07-11-2-v2-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-11-2-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-11-2-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v2/nvidia
albertwang8192-2025-07-11-2-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v2/nvidia/config.json
albertwang8192-2025-07-11-2-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v2/nvidia/special_tokens_map.json
albertwang8192-2025-07-11-2-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v2/nvidia/tokenizer_config.json
albertwang8192-2025-07-11-2-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v2/nvidia/tokenizer.json
albertwang8192-2025-07-11-2-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v2/nvidia/flywheel_model.0.safetensors
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Job albertwang8192-2025-07-11-2-v2-mkmlizer completed after 85.15s with status: succeeded
Stopping job with name albertwang8192-2025-07-11-2-v2-mkmlizer
Pipeline stage MKMLizer completed in 85.65s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.14s
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Running pipeline stage MKMLDeployer
Creating inference service albertwang8192-2025-07-11-2-v2
Waiting for inference service albertwang8192-2025-07-11-2-v2 to be ready
Inference service albertwang8192-2025-07-11-2-v2 ready after 200.97394371032715s
Pipeline stage MKMLDeployer completed in 201.46s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.2936012744903564s
Received healthy response to inference request in 1.8283379077911377s
Received healthy response to inference request in 1.7839269638061523s
Received healthy response to inference request in 1.7615416049957275s
Received healthy response to inference request in 1.679208517074585s
5 requests
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5th percentile: 1.6956751346588135
10th percentile: 1.712141752243042
20th percentile: 1.745074987411499
30th percentile: 1.7660186767578125
40th percentile: 1.7749728202819823
50th percentile: 1.7839269638061523
60th percentile: 1.8016913414001465
70th percentile: 1.8194557189941407
80th percentile: 1.9213905811309815
90th percentile: 2.107495927810669
95th percentile: 2.2005486011505124
99th percentile: 2.2749907398223876
mean time: 1.8693232536315918
Pipeline stage StressChecker completed in 10.87s
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