junhua024-chai-16-full-_94000

developer_uid: junhua024
submission_id: junhua024-chai-16-full-_94000_v5
model_name: junhua024-chai-16-full-_94000_v5
model_group: junhua024/chai_16_full_q
status: torndown
timestamp: 2025-07-20T13:17:24+00:00
num_battles: 7699
num_wins: 3742
celo_rating: 1277.9
family_friendly_score: 0.5548
family_friendly_standard_error: 0.007028470103799261
submission_type: basic
model_repo: junhua024/chai_16_full_qkv100_o106_ffn106_1925
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': 0.5864740726967849, 'latency_mean': 1.7049755048751831, 'latency_p50': 1.698011875152588, 'latency_p90': 1.8835266828536987}, {'batch_size': 3, 'throughput': 1.0326951647041591, 'latency_mean': 2.892393435239792, 'latency_p50': 2.9026681184768677, 'latency_p90': 3.143150734901428}, {'batch_size': 5, 'throughput': 1.2396813392742692, 'latency_mean': 4.013773696422577, 'latency_p50': 4.016695618629456, 'latency_p90': 4.49858341217041}, {'batch_size': 6, 'throughput': 1.309446305670494, 'latency_mean': 4.548947311639786, 'latency_p50': 4.514304161071777, 'latency_p90': 5.076657605171204}, {'batch_size': 8, 'throughput': 1.3770915705364555, 'latency_mean': 5.7665561735630035, 'latency_p50': 5.731870532035828, 'latency_p90': 6.4955837488174435}, {'batch_size': 10, 'throughput': 1.3965105076985587, 'latency_mean': 7.10256223320961, 'latency_p50': 7.0841251611709595, 'latency_p90': 7.98233699798584}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-16-full-_94000_v5
is_internal_developer: False
language_model: junhua024/chai_16_full_qkv100_o106_ffn106_1925
model_size: 13B
ranking_group: single
throughput_3p7s: 1.2
us_pacific_date: 2025-07-20
win_ratio: 0.48603714768151707
generation_params: {'temperature': 1.0, 'top_p': 0.88, 'min_p': 0.0, 'top_k': 10, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\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
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name junhua024-chai-16-full-94000-v5-mkmlizer
Waiting for job on junhua024-chai-16-full-94000-v5-mkmlizer to finish
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junhua024-chai-16-full-94000-v5-mkmlizer: ║                                                                     ║
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junhua024-chai-16-full-94000-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-16-full-94000-v5-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-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`
junhua024-chai-16-full-94000-v5-mkmlizer: Downloaded to shared memory in 116.284s
junhua024-chai-16-full-94000-v5-mkmlizer: Checking if junhua024/chai_16_full_qkv100_o106_ffn106_1925 already exists in ChaiML
junhua024-chai-16-full-94000-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp2e16ynhn, device:0
junhua024-chai-16-full-94000-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
junhua024-chai-16-full-94000-v5-mkmlizer: quantized model in 31.882s
junhua024-chai-16-full-94000-v5-mkmlizer: Processed model junhua024/chai_16_full_qkv100_o106_ffn106_1925 in 148.256s
junhua024-chai-16-full-94000-v5-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-16-full-94000-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-16-full-94000-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v5/nvidia
junhua024-chai-16-full-94000-v5-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v5/nvidia/flywheel_model.0.safetensors
junhua024-chai-16-full-94000-v5-mkmlizer: 
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Job junhua024-chai-16-full-94000-v5-mkmlizer completed after 183.48s with status: succeeded
Stopping job with name junhua024-chai-16-full-94000-v5-mkmlizer
Pipeline stage MKMLizer completed in 184.27s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.17s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service junhua024-chai-16-full-94000-v5
Waiting for inference service junhua024-chai-16-full-94000-v5 to be ready
Failed to get response for submission chaiml-nis-qwen32b-sim_98336_v34: HTTPConnectionPool(host='chaiml-nis-qwen32b-sim-98336-v34-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
Failed to get response for submission mistralai-mistral-nem_93303_v521: HTTPConnectionPool(host='mistralai-mistral-nem-93303-v521-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
Failed to get response for submission chaiml-nis-qwen32b-sim_98336_v34: HTTPConnectionPool(host='chaiml-nis-qwen32b-sim-98336-v34-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
Failed to get response for submission chaiml-nis-qwen32b-sim_98336_v34: HTTPConnectionPool(host='chaiml-nis-qwen32b-sim-98336-v34-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
Inference service junhua024-chai-16-full-94000-v5 ready after 331.51598954200745s
Pipeline stage MKMLDeployer completed in 332.07s
run pipeline stage %s
Running pipeline stage StressChecker
HTTPConnectionPool(host='guanaco-submitter.guanaco-backend.k2.chaiverse.com', port=80): Read timed out. (read timeout=20)
Received unhealthy response to inference request!
Received healthy response to inference request in 2.673750162124634s
Received healthy response to inference request in 1.6622858047485352s
Received healthy response to inference request in 2.211472988128662s
Received healthy response to inference request in 1.9208991527557373s
5 requests
1 failed requests
5th percentile: 1.7140084743499755
10th percentile: 1.765731143951416
20th percentile: 1.869176483154297
30th percentile: 1.9790139198303223
40th percentile: 2.095243453979492
50th percentile: 2.211472988128662
60th percentile: 2.396383857727051
70th percentile: 2.581294727325439
80th percentile: 6.167059183120731
90th percentile: 13.153677225112917
95th percentile: 16.646986246109005
99th percentile: 19.441633462905884
mean time: 5.721740674972534
%s, retrying in %s seconds...
Received healthy response to inference request in 1.7050745487213135s
Received healthy response to inference request in 1.7198681831359863s
Received healthy response to inference request in 1.6403963565826416s
Received healthy response to inference request in 2.049168586730957s
Received healthy response to inference request in 1.9928786754608154s
5 requests
0 failed requests
5th percentile: 1.653331995010376
10th percentile: 1.6662676334381104
20th percentile: 1.692138910293579
30th percentile: 1.708033275604248
40th percentile: 1.7139507293701173
50th percentile: 1.7198681831359863
60th percentile: 1.8290723800659179
70th percentile: 1.9382765769958497
80th percentile: 2.004136657714844
90th percentile: 2.0266526222229
95th percentile: 2.0379106044769286
99th percentile: 2.046916990280151
mean time: 1.8214772701263429
Pipeline stage StressChecker completed in 40.52s
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 1.26s
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 0.76s
Shutdown handler de-registered
junhua024-chai-16-full-_94000_v5 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.12s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service junhua024-chai-16-full-94000-v5-profiler
Waiting for inference service junhua024-chai-16-full-94000-v5-profiler to be ready
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 4571.78s
Shutdown handler de-registered
junhua024-chai-16-full-_94000_v5 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-16-full-_94000_v5 status is now torndown due to DeploymentManager action