junhua024-chai-06-full-_75415

developer_uid: junhua024
submission_id: junhua024-chai-06-full-_75415_v5
model_name: junhua024-chai-06-full-_75415_v5
model_group: junhua024/chai_06_full_0
status: torndown
timestamp: 2025-07-17T20:27:45+00:00
num_battles: 6394
num_wins: 3142
celo_rating: 1284.13
family_friendly_score: 0.0
family_friendly_standard_error: 0.0
submission_type: basic
model_repo: junhua024/chai_06_full_02102_20241
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': 0.5906824344903678, 'latency_mean': 1.6928384292125702, 'latency_p50': 1.6915675401687622, 'latency_p90': 1.853171944618225}, {'batch_size': 3, 'throughput': 1.0685974787897978, 'latency_mean': 2.7953611612319946, 'latency_p50': 2.7990177869796753, 'latency_p90': 3.080518126487732}, {'batch_size': 5, 'throughput': 1.2774001507600576, 'latency_mean': 3.893285380601883, 'latency_p50': 3.8919941186904907, 'latency_p90': 4.364297032356262}, {'batch_size': 6, 'throughput': 1.3571248968102496, 'latency_mean': 4.401498130559921, 'latency_p50': 4.434580087661743, 'latency_p90': 4.9008633852005}, {'batch_size': 8, 'throughput': 1.4164939668645387, 'latency_mean': 5.60741907954216, 'latency_p50': 5.574854612350464, 'latency_p90': 6.305159568786621}, {'batch_size': 10, 'throughput': 1.4481375859420655, 'latency_mean': 6.850348027944565, 'latency_p50': 6.8003034591674805, 'latency_p90': 7.788423299789429}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-06-full-_75415_v5
is_internal_developer: False
language_model: junhua024/chai_06_full_02102_20241
model_size: 13B
ranking_group: single
throughput_3p7s: 1.26
us_pacific_date: 2025-07-17
win_ratio: 0.49139818579918676
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-06-full-75415-v5-mkmlizer
Waiting for job on junhua024-chai-06-full-75415-v5-mkmlizer to finish
junhua024-chai-06-full-75415-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
junhua024-chai-06-full-75415-v5-mkmlizer: ║                                                                     ║
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junhua024-chai-06-full-75415-v5-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-06-full-75415-v5-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-75415-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-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-06-full-75415-v5-mkmlizer: Downloaded to shared memory in 75.002s
junhua024-chai-06-full-75415-v5-mkmlizer: Checking if junhua024/chai_06_full_02102_20241 already exists in ChaiML
junhua024-chai-06-full-75415-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmppn69a92f, device:0
junhua024-chai-06-full-75415-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
junhua024-chai-06-full-75415-v5-mkmlizer: quantized model in 31.207s
junhua024-chai-06-full-75415-v5-mkmlizer: Processed model junhua024/chai_06_full_02102_20241 in 106.316s
junhua024-chai-06-full-75415-v5-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-06-full-75415-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-06-full-75415-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-06-full-75415-v5/nvidia
junhua024-chai-06-full-75415-v5-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-06-full-75415-v5/nvidia/config.json
junhua024-chai-06-full-75415-v5-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-06-full-75415-v5/nvidia/special_tokens_map.json
junhua024-chai-06-full-75415-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-06-full-75415-v5/nvidia/tokenizer_config.json
junhua024-chai-06-full-75415-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-06-full-75415-v5/nvidia/tokenizer.json
junhua024-chai-06-full-75415-v5-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-06-full-75415-v5/nvidia/flywheel_model.0.safetensors
junhua024-chai-06-full-75415-v5-mkmlizer: 
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Job junhua024-chai-06-full-75415-v5-mkmlizer completed after 132.44s with status: succeeded
Stopping job with name junhua024-chai-06-full-75415-v5-mkmlizer
Pipeline stage MKMLizer completed in 133.12s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.24s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service junhua024-chai-06-full-75415-v5
Waiting for inference service junhua024-chai-06-full-75415-v5 to be ready
Inference service junhua024-chai-06-full-75415-v5 ready after 312.7251205444336s
Pipeline stage MKMLDeployer completed in 313.56s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.452862024307251s
Received healthy response to inference request in 1.674868106842041s
Received healthy response to inference request in 1.7953007221221924s
Received healthy response to inference request in 1.6160061359405518s
Received healthy response to inference request in 1.9177272319793701s
5 requests
0 failed requests
5th percentile: 1.6277785301208496
10th percentile: 1.6395509243011475
20th percentile: 1.6630957126617432
30th percentile: 1.6989546298980713
40th percentile: 1.7471276760101317
50th percentile: 1.7953007221221924
60th percentile: 1.8442713260650634
70th percentile: 1.8932419300079346
80th percentile: 2.024754190444946
90th percentile: 2.238808107376099
95th percentile: 2.345835065841675
99th percentile: 2.4314566326141356
mean time: 1.8913528442382812
Pipeline stage StressChecker completed in 11.03s
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Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
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starting trigger_guanaco_pipeline args=%s
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Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.76s
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Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 0.70s
Shutdown handler de-registered
junhua024-chai-06-full-_75415_v5 status is now deployed due to DeploymentManager action
Shutdown handler registered
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
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Creating inference service junhua024-chai-06-full-75415-v5-profiler
Waiting for inference service junhua024-chai-06-full-75415-v5-profiler to be ready
Inference service junhua024-chai-06-full-75415-v5-profiler ready after 314.3703236579895s
Pipeline stage MKMLProfilerDeployer completed in 315.34s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/junhua024-chai-06-fub9e0012f6897d930a821fdbb2fcba1e3-deplozbbwp:/code/chaiverse_profiler_1752784905 --namespace tenant-chaiml-guanaco
kubectl exec -it junhua024-chai-06-fub9e0012f6897d930a821fdbb2fcba1e3-deplozbbwp --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1752784905 && python profiles.py profile --best_of_n 8 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 1024 --output_tokens 64 --summary /code/chaiverse_profiler_1752784905/summary.json'
kubectl exec -it junhua024-chai-06-fub9e0012f6897d930a821fdbb2fcba1e3-deplozbbwp --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1752784905/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1121.96s
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Running pipeline stage MKMLProfilerDeleter
Checking if service junhua024-chai-06-full-75415-v5-profiler is running
Tearing down inference service junhua024-chai-06-full-75415-v5-profiler
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Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
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Evaluating %s Family Friendly Score with %s threads
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clean up pipeline due to error=DeploymentChecksError('None: None')
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junhua024-chai-06-full-_75415_v5 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-06-full-_75415_v5 status is now torndown due to DeploymentManager action
junhua024-chai-06-full-_75415_v5 status is now torndown due to DeploymentManager action