developer_uid: RandomForest1024
submission_id: albertwang8192-2025-07-11-2_v7
model_name: 2025-07-11_2_v7
model_group: AlbertWang8192/2025-07-1
status: torndown
timestamp: 2025-07-12T05:05:17+00:00
num_battles: 8680
num_wins: 4352
celo_rating: 1273.26
family_friendly_score: 0.5347999999999999
family_friendly_standard_error: 0.007053920328441483
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': 0.5889805547678847, 'latency_mean': 1.6977282691001891, 'latency_p50': 1.7105262279510498, 'latency_p90': 1.8680243253707884}, {'batch_size': 3, 'throughput': 1.0709120788213415, 'latency_mean': 2.7950163531303405, 'latency_p50': 2.783874273300171, 'latency_p90': 3.1095836877822878}, {'batch_size': 5, 'throughput': 1.2827750443058619, 'latency_mean': 3.886336224079132, 'latency_p50': 3.8967963457107544, 'latency_p90': 4.364188289642334}, {'batch_size': 6, 'throughput': 1.3497937102163946, 'latency_mean': 4.419786654710769, 'latency_p50': 4.378408312797546, 'latency_p90': 4.969783806800842}, {'batch_size': 8, 'throughput': 1.408005944107125, 'latency_mean': 5.652763044834137, 'latency_p50': 5.694935321807861, 'latency_p90': 6.365919494628907}, {'batch_size': 10, 'throughput': 1.4349984413655938, 'latency_mean': 6.909724276065827, 'latency_p50': 6.877404808998108, 'latency_p90': 7.812040138244629}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: 2025-07-11_2_v7
is_internal_developer: False
language_model: AlbertWang8192/2025-07-11_2
model_size: 13B
ranking_group: single
throughput_3p7s: 1.26
us_pacific_date: 2025-07-11
win_ratio: 0.5013824884792627
generation_params: {'temperature': 0.6, 'top_p': 0.95, 'min_p': 0.025, 'top_k': 60, 'presence_penalty': 0.3, 'frequency_penalty': 0.3, '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-v7-mkmlizer
Waiting for job on albertwang8192-2025-07-11-2-v7-mkmlizer to finish
albertwang8192-2025-07-11-2-v7-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
albertwang8192-2025-07-11-2-v7-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-11-2-v7-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-2-v7-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-11-2-v7-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-v7-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-v7-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-v7-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-v7-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-v7-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-v7-mkmlizer: Downloaded to shared memory in 30.552s
albertwang8192-2025-07-11-2-v7-mkmlizer: Checking if AlbertWang8192/2025-07-11_2 already exists in ChaiML
albertwang8192-2025-07-11-2-v7-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpbwqem2v7, device:0
albertwang8192-2025-07-11-2-v7-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-11-2-v7-mkmlizer: quantized model in 31.629s
albertwang8192-2025-07-11-2-v7-mkmlizer: Processed model AlbertWang8192/2025-07-11_2 in 62.260s
albertwang8192-2025-07-11-2-v7-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-11-2-v7-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-11-2-v7-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v7/nvidia
albertwang8192-2025-07-11-2-v7-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v7/nvidia/config.json
albertwang8192-2025-07-11-2-v7-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v7/nvidia/special_tokens_map.json
albertwang8192-2025-07-11-2-v7-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v7/nvidia/tokenizer_config.json
albertwang8192-2025-07-11-2-v7-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v7/nvidia/tokenizer.json
albertwang8192-2025-07-11-2-v7-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-11-2-v7/nvidia/flywheel_model.0.safetensors
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Job albertwang8192-2025-07-11-2-v7-mkmlizer completed after 86.79s with status: succeeded
Stopping job with name albertwang8192-2025-07-11-2-v7-mkmlizer
Pipeline stage MKMLizer completed in 87.48s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
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Running pipeline stage MKMLDeployer
Creating inference service albertwang8192-2025-07-11-2-v7
Waiting for inference service albertwang8192-2025-07-11-2-v7 to be ready
Inference service albertwang8192-2025-07-11-2-v7 ready after 200.72498512268066s
Pipeline stage MKMLDeployer completed in 201.27s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.41144061088562s
Received healthy response to inference request in 1.6321499347686768s
Received healthy response to inference request in 1.5019862651824951s
Received healthy response to inference request in 1.5748109817504883s
Received healthy response to inference request in 2.0429422855377197s
5 requests
0 failed requests
5th percentile: 1.5165512084960937
10th percentile: 1.5311161518096923
20th percentile: 1.5602460384368897
30th percentile: 1.586278772354126
40th percentile: 1.6092143535614014
50th percentile: 1.6321499347686768
60th percentile: 1.796466875076294
70th percentile: 1.960783815383911
80th percentile: 2.1166419506073
90th percentile: 2.26404128074646
95th percentile: 2.33774094581604
99th percentile: 2.396700677871704
mean time: 1.832666015625
Pipeline stage StressChecker completed in 10.53s
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Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
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Running pipeline stage TriggerMKMLProfilingPipeline
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Pipeline stage TriggerMKMLProfilingPipeline completed in 0.68s
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Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 3095.49s
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albertwang8192-2025-07-11-2_v7 status is now inactive due to auto deactivation removed underperforming models
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