junhua024-chai-02-full_54657

developer_uid: junhua024
submission_id: junhua024-chai-02-full_54657_v15
model_name: junhua024-chai-02-full_54657_v15
model_group: junhua024/chai_02_full_0
status: torndown
timestamp: 2025-07-24T10:31:00+00:00
num_battles: 5695
num_wins: 2877
celo_rating: 1281.02
family_friendly_score: 0.41579999999999995
family_friendly_standard_error: 0.006970084074098389
submission_type: basic
model_repo: junhua024/chai_02_full_02_019
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': 0.6670299558902828, 'latency_mean': 1.4990558981895448, 'latency_p50': 1.4982082843780518, 'latency_p90': 1.6442311763763429}, {'batch_size': 3, 'throughput': 1.153300094557704, 'latency_mean': 2.5945809948444367, 'latency_p50': 2.585834503173828, 'latency_p90': 2.9198755025863647}, {'batch_size': 5, 'throughput': 1.3366987038023392, 'latency_mean': 3.7279852378368377, 'latency_p50': 3.6927812099456787, 'latency_p90': 4.1738609790802}, {'batch_size': 6, 'throughput': 1.3800603290742703, 'latency_mean': 4.3185618102550505, 'latency_p50': 4.294185519218445, 'latency_p90': 4.880432343482971}, {'batch_size': 8, 'throughput': 1.4381028643828702, 'latency_mean': 5.523837987184525, 'latency_p50': 5.552316069602966, 'latency_p90': 6.169621253013611}, {'batch_size': 10, 'throughput': 1.4552108351738906, 'latency_mean': 6.820725607872009, 'latency_p50': 6.866399645805359, 'latency_p90': 7.662651515007019}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-02-full_54657_v15
is_internal_developer: False
language_model: junhua024/chai_02_full_02_019
model_size: 13B
ranking_group: single
throughput_3p7s: 1.34
us_pacific_date: 2025-07-24
win_ratio: 0.5051799824407375
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 20, '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': "{memory} You are an empathetic conversational AI. You understand the user's feelings and respond with warmth, compassion, and sincerity.", '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-02-full-54657-v15-mkmlizer
Waiting for job on junhua024-chai-02-full-54657-v15-mkmlizer to finish
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junhua024-chai-02-full-54657-v15-mkmlizer: ║                                                                     ║
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junhua024-chai-02-full-54657-v15-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║                                                                     ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║                                                                     ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║                                                                     ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-02-full-54657-v15-mkmlizer: ║                                                                     ║
junhua024-chai-02-full-54657-v15-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-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-02-full-54657-v15-mkmlizer: Downloaded to shared memory in 87.321s
junhua024-chai-02-full-54657-v15-mkmlizer: Checking if junhua024/chai_02_full_02_019 already exists in ChaiML
junhua024-chai-02-full-54657-v15-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmp7vlsk7wz, device:0
junhua024-chai-02-full-54657-v15-mkmlizer: Saving flywheel model at /dev/shm/model_cache
junhua024-chai-02-full-54657-v15-mkmlizer: quantized model in 207.899s
junhua024-chai-02-full-54657-v15-mkmlizer: Processed model junhua024/chai_02_full_02_019 in 295.308s
junhua024-chai-02-full-54657-v15-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-02-full-54657-v15-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-02-full-54657-v15-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-02-full-54657-v15/nvidia
junhua024-chai-02-full-54657-v15-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-02-full-54657-v15/nvidia/config.json
junhua024-chai-02-full-54657-v15-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-02-full-54657-v15/nvidia/special_tokens_map.json
junhua024-chai-02-full-54657-v15-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-02-full-54657-v15/nvidia/tokenizer_config.json
junhua024-chai-02-full-54657-v15-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-02-full-54657-v15/nvidia/tokenizer.json
junhua024-chai-02-full-54657-v15-mkmlizer: 
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Job junhua024-chai-02-full-54657-v15-mkmlizer completed after 325.78s with status: succeeded
Stopping job with name junhua024-chai-02-full-54657-v15-mkmlizer
Pipeline stage MKMLizer completed in 326.42s
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-02-full-54657-v15
Waiting for inference service junhua024-chai-02-full-54657-v15 to be ready
Failed to get response for submission chaiml-next-door-annoyi_15417_v1: ('http://chaiml-next-door-annoyi-15417-v1-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
Failed to get response for submission chaiml-next-door-annoyi_15417_v1: ('http://chaiml-next-door-annoyi-15417-v1-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
Inference service junhua024-chai-02-full-54657-v15 ready after 180.67795395851135s
Pipeline stage MKMLDeployer completed in 181.20s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.2010796070098877s
Received healthy response to inference request in 1.759246587753296s
Received healthy response to inference request in 2.7653439044952393s
Received healthy response to inference request in 1.0577919483184814s
Received healthy response to inference request in 2.1969525814056396s
5 requests
0 failed requests
5th percentile: 1.1980828762054443
10th percentile: 1.3383738040924071
20th percentile: 1.618955659866333
30th percentile: 1.8467877864837647
40th percentile: 2.021870183944702
50th percentile: 2.1969525814056396
60th percentile: 2.4243091106414796
70th percentile: 2.651665639877319
80th percentile: 2.852491044998169
90th percentile: 3.0267853260040285
95th percentile: 3.113932466506958
99th percentile: 3.1836501789093017
mean time: 2.196082925796509
Pipeline stage StressChecker completed in 12.60s
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 0.72s
Shutdown handler de-registered
junhua024-chai-02-full_54657_v15 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 0.15s
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-02-full-54657-v15-profiler
Waiting for inference service junhua024-chai-02-full-54657-v15-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
Pipeline stage OfflineFamilyFriendlyScorer completed in 3155.05s
Shutdown handler de-registered
junhua024-chai-02-full_54657_v15 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-02-full_54657_v15 status is now torndown due to DeploymentManager action