junhua024-chai-16-full-_69709

developer_uid: junhua024
submission_id: junhua024-chai-16-full-_69709_v6
model_name: junhua024-chai-16-full-_69709_v6
model_group: junhua024/chai_16_full_1
status: torndown
timestamp: 2025-07-19T18:02:26+00:00
num_battles: 8195
num_wins: 3973
celo_rating: 1275.64
family_friendly_score: 0.5569999999999999
family_friendly_standard_error: 0.007024969750824553
submission_type: basic
model_repo: junhua024/chai_16_full_104_o_ffn_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': 0.6051723401359532, 'latency_mean': 1.652318642139435, 'latency_p50': 1.646759033203125, 'latency_p90': 1.8311157703399659}, {'batch_size': 3, 'throughput': 1.0973724707164036, 'latency_mean': 2.7238499569892882, 'latency_p50': 2.7174102067947388, 'latency_p90': 3.0461636781692505}, {'batch_size': 5, 'throughput': 1.3078116068105492, 'latency_mean': 3.799373159408569, 'latency_p50': 3.7910847663879395, 'latency_p90': 4.2179741859436035}, {'batch_size': 6, 'throughput': 1.376086104646785, 'latency_mean': 4.329621509313584, 'latency_p50': 4.392953157424927, 'latency_p90': 4.811705183982849}, {'batch_size': 8, 'throughput': 1.4399293218285758, 'latency_mean': 5.510152589082718, 'latency_p50': 5.548734426498413, 'latency_p90': 6.136085367202758}, {'batch_size': 10, 'throughput': 1.4753636152889291, 'latency_mean': 6.71224971652031, 'latency_p50': 6.651133418083191, 'latency_p90': 7.617745399475098}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-16-full-_69709_v6
is_internal_developer: False
language_model: junhua024/chai_16_full_104_o_ffn_1925
model_size: 13B
ranking_group: single
throughput_3p7s: 1.3
us_pacific_date: 2025-07-19
win_ratio: 0.4848078096400244
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-69709-v6-mkmlizer
Waiting for job on junhua024-chai-16-full-69709-v6-mkmlizer to finish
junhua024-chai-16-full-69709-v6-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
junhua024-chai-16-full-69709-v6-mkmlizer: ║                                                                     ║
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junhua024-chai-16-full-69709-v6-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-16-full-69709-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-69709-v6-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-16-full-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-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-69709-v6-mkmlizer: Downloaded to shared memory in 77.429s
junhua024-chai-16-full-69709-v6-mkmlizer: Checking if junhua024/chai_16_full_104_o_ffn_1925 already exists in ChaiML
junhua024-chai-16-full-69709-v6-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmprwv26qdx, device:0
junhua024-chai-16-full-69709-v6-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Failed to get response for submission junhua024-chai-16-full-_74386_v3: HTTPConnectionPool(host='junhua024-chai-16-full-74386-v3-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
junhua024-chai-16-full-69709-v6-mkmlizer: quantized model in 32.127s
junhua024-chai-16-full-69709-v6-mkmlizer: Processed model junhua024/chai_16_full_104_o_ffn_1925 in 109.633s
junhua024-chai-16-full-69709-v6-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-16-full-69709-v6-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-16-full-69709-v6/nvidia/config.json
junhua024-chai-16-full-69709-v6-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-16-full-69709-v6/nvidia/special_tokens_map.json
junhua024-chai-16-full-69709-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-16-full-69709-v6/nvidia/tokenizer_config.json
junhua024-chai-16-full-69709-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-16-full-69709-v6/nvidia/tokenizer.json
junhua024-chai-16-full-69709-v6-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-16-full-69709-v6/nvidia/flywheel_model.0.safetensors
junhua024-chai-16-full-69709-v6-mkmlizer: 
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Job junhua024-chai-16-full-69709-v6-mkmlizer completed after 139.49s with status: succeeded
Stopping job with name junhua024-chai-16-full-69709-v6-mkmlizer
Pipeline stage MKMLizer completed in 140.10s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.19s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service junhua024-chai-16-full-69709-v6
Waiting for inference service junhua024-chai-16-full-69709-v6 to be ready
Failed to get response for submission junhua024-chai-16-full-_74386_v3: HTTPConnectionPool(host='junhua024-chai-16-full-74386-v3-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-69709-v6 ready after 331.75803089141846s
Pipeline stage MKMLDeployer completed in 332.35s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.842334032058716s
Received healthy response to inference request in 2.135249376296997s
Received healthy response to inference request in 1.7061173915863037s
Received healthy response to inference request in 1.839660406112671s
Received healthy response to inference request in 1.6008305549621582s
5 requests
0 failed requests
5th percentile: 1.6218879222869873
10th percentile: 1.6429452896118164
20th percentile: 1.6850600242614746
30th percentile: 1.7328259944915771
40th percentile: 1.786243200302124
50th percentile: 1.839660406112671
60th percentile: 1.9578959941864014
70th percentile: 2.076131582260132
80th percentile: 2.276666307449341
90th percentile: 2.5595001697540285
95th percentile: 2.7009171009063717
99th percentile: 2.814050645828247
mean time: 2.024838352203369
Pipeline stage StressChecker completed in 11.84s
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Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.82s
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Running pipeline stage TriggerMKMLProfilingPipeline
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Pipeline stage TriggerMKMLProfilingPipeline completed in 0.95s
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junhua024-chai-16-full-_69709_v6 status is now deployed due to DeploymentManager action
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
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Pipeline stage MKMLProfilerTemplater completed in 0.11s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service junhua024-chai-16-full-69709-v6-profiler
Waiting for inference service junhua024-chai-16-full-69709-v6-profiler to be ready
Inference service junhua024-chai-16-full-69709-v6-profiler ready after 323.7832200527191s
Pipeline stage MKMLProfilerDeployer completed in 324.78s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/junhua024-chai-16-fub50458a10905d8b0d7777a43ce90d9c3-deplo6qzzj:/code/chaiverse_profiler_1752949038 --namespace tenant-chaiml-guanaco
kubectl exec -it junhua024-chai-16-fub50458a10905d8b0d7777a43ce90d9c3-deplo6qzzj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1752949038 && 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_1752949038/summary.json'
kubectl exec -it junhua024-chai-16-fub50458a10905d8b0d7777a43ce90d9c3-deplo6qzzj --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1752949038/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1095.69s
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Running pipeline stage MKMLProfilerDeleter
Checking if service junhua024-chai-16-full-69709-v6-profiler is running
Tearing down inference service junhua024-chai-16-full-69709-v6-profiler
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Pipeline stage MKMLProfilerDeleter completed in 4.90s
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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
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Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 5468.70s
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junhua024-chai-16-full-_69709_v6 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-16-full-_69709_v6 status is now torndown due to DeploymentManager action