developer_uid: RandomForest1024
submission_id: albertwang8192-2025-07-11-7_v14
model_name: 2025-07-11_7_V14
model_group: AlbertWang8192/2025-07-1
status: torndown
timestamp: 2025-07-13T17:41:09+00:00
num_battles: 7757
num_wins: 3680
celo_rating: 1261.72
family_friendly_score: 0.546
family_friendly_standard_error: 0.007041079462696043
submission_type: basic
model_repo: AlbertWang8192/2025-07-11_7
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': 0.5956027042049536, 'latency_mean': 1.6788360321521758, 'latency_p50': 1.6606017351150513, 'latency_p90': 1.8653333187103271}, {'batch_size': 3, 'throughput': 1.0496210985436354, 'latency_mean': 2.8472521138191222, 'latency_p50': 2.8585842847824097, 'latency_p90': 3.125025677680969}, {'batch_size': 5, 'throughput': 1.2488299580869866, 'latency_mean': 3.98716668844223, 'latency_p50': 4.002113461494446, 'latency_p90': 4.458902359008789}, {'batch_size': 6, 'throughput': 1.3145719711138701, 'latency_mean': 4.542150138616562, 'latency_p50': 4.573156952857971, 'latency_p90': 5.07000663280487}, {'batch_size': 8, 'throughput': 1.39124191477819, 'latency_mean': 5.710684334039688, 'latency_p50': 5.675916790962219, 'latency_p90': 6.5066595554351805}, {'batch_size': 10, 'throughput': 1.4021008446874823, 'latency_mean': 7.065633308887482, 'latency_p50': 7.026511311531067, 'latency_p90': 7.894674086570739}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: 2025-07-11_7_V14
is_internal_developer: False
language_model: AlbertWang8192/2025-07-11_7
model_size: 13B
ranking_group: single
throughput_3p7s: 1.22
us_pacific_date: 2025-07-13
win_ratio: 0.4744102101327833
generation_params: {'temperature': 0.6, 'top_p': 0.99, 'min_p': 0.05, 'top_k': 40, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['<|im_start|>', '<|im_end|>', '\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': '<|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{bot_name}:', 'truncate_by_message': True}
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
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Running pipeline stage MKMLizer
Starting job with name albertwang8192-2025-07-11-7-v14-mkmlizer
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albertwang8192-2025-07-11-7-v14-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-11-7-v14-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v14-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-11-7-v14-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`
albertwang8192-2025-07-11-7-v14-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`
albertwang8192-2025-07-11-7-v14-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`
albertwang8192-2025-07-11-7-v14-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`
albertwang8192-2025-07-11-7-v14-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`
albertwang8192-2025-07-11-7-v14-mkmlizer: Downloaded to shared memory in 36.345s
albertwang8192-2025-07-11-7-v14-mkmlizer: Checking if AlbertWang8192/2025-07-11_7 already exists in ChaiML
albertwang8192-2025-07-11-7-v14-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmprpdiq_ux, device:0
albertwang8192-2025-07-11-7-v14-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-11-7-v14-mkmlizer: quantized model in 38.395s
albertwang8192-2025-07-11-7-v14-mkmlizer: Processed model AlbertWang8192/2025-07-11_7 in 74.868s
albertwang8192-2025-07-11-7-v14-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-11-7-v14-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-11-7-v14-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v14/nvidia
albertwang8192-2025-07-11-7-v14-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v14/nvidia/config.json
albertwang8192-2025-07-11-7-v14-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v14/nvidia/special_tokens_map.json
albertwang8192-2025-07-11-7-v14-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v14/nvidia/flywheel_model.0.safetensors
Job albertwang8192-2025-07-11-7-v14-mkmlizer completed after 106.61s with status: succeeded
Stopping job with name albertwang8192-2025-07-11-7-v14-mkmlizer
Pipeline stage MKMLizer completed in 107.45s
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Creating inference service albertwang8192-2025-07-11-7-v14
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Failed to get response for submission albertwang8192-2025-07-13-1_v1: HTTPConnectionPool(host='albertwang8192-2025-07-13-1-v1-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
Inference service albertwang8192-2025-07-11-7-v14 ready after 221.40897345542908s
Pipeline stage MKMLDeployer completed in 222.24s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.5961079597473145s
Received healthy response to inference request in 1.6329460144042969s
Received healthy response to inference request in 1.7241241931915283s
Received healthy response to inference request in 1.5054233074188232s
Received healthy response to inference request in 1.7171154022216797s
5 requests
0 failed requests
5th percentile: 1.530927848815918
10th percentile: 1.5564323902130126
20th percentile: 1.6074414730072022
30th percentile: 1.6497798919677735
40th percentile: 1.6834476470947266
50th percentile: 1.7171154022216797
60th percentile: 1.719918918609619
70th percentile: 1.7227224349975585
80th percentile: 1.8985209465026858
90th percentile: 2.247314453125
95th percentile: 2.4217112064361572
99th percentile: 2.561228609085083
mean time: 1.8351433753967286
Pipeline stage StressChecker completed in 10.54s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 1.04s
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Evaluating %s Family Friendly Score with %s threads
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Pipeline stage OfflineFamilyFriendlyScorer completed in 5838.04s
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albertwang8192-2025-07-11-7_v14 status is now inactive due to auto deactivation removed underperforming models
albertwang8192-2025-07-11-7_v14 status is now torndown due to DeploymentManager action