developer_uid: RandomForest1024
submission_id: albertwang8192-2025-07-12-0_v1
model_name: 2025-07-12_0
model_group: AlbertWang8192/2025-07-1
status: torndown
timestamp: 2025-07-13T00:11:15+00:00
num_battles: 8951
num_wins: 4190
celo_rating: 1261.63
family_friendly_score: 0.5594
family_friendly_standard_error: 0.007020991952708677
submission_type: basic
model_repo: AlbertWang8192/2025-07-12_0
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': 0.5958607066691697, 'latency_mean': 1.6781236946582794, 'latency_p50': 1.6627483367919922, 'latency_p90': 1.8735332489013672}, {'batch_size': 3, 'throughput': 1.0399215402595157, 'latency_mean': 2.876272495985031, 'latency_p50': 2.8981722593307495, 'latency_p90': 3.1531785488128663}, {'batch_size': 5, 'throughput': 1.257778561531673, 'latency_mean': 3.9527885222435, 'latency_p50': 3.974554181098938, 'latency_p90': 4.362275767326355}, {'batch_size': 6, 'throughput': 1.3212255265908581, 'latency_mean': 4.515408890247345, 'latency_p50': 4.495846390724182, 'latency_p90': 5.078120112419128}, {'batch_size': 8, 'throughput': 1.37353800747198, 'latency_mean': 5.77505264878273, 'latency_p50': 5.776060461997986, 'latency_p90': 6.44901864528656}, {'batch_size': 10, 'throughput': 1.4147605562373928, 'latency_mean': 7.018265221118927, 'latency_p50': 7.04116952419281, 'latency_p90': 7.859968042373657}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: 2025-07-12_0
is_internal_developer: False
language_model: AlbertWang8192/2025-07-12_0
model_size: 13B
ranking_group: single
throughput_3p7s: 1.22
us_pacific_date: 2025-07-12
win_ratio: 0.4681041224444196
generation_params: {'temperature': 0.6, 'top_p': 0.98, 'min_p': 0.05, 'top_k': 40, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['<|im_end|>', '<|im_start|>', '\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 albertwang8192-2025-07-12-0-v1-mkmlizer
Waiting for job on albertwang8192-2025-07-12-0-v1-mkmlizer to finish
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albertwang8192-2025-07-12-0-v1-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-12-0-v1-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-12-0-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-12-0-v1-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`
albertwang8192-2025-07-12-0-v1-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`
albertwang8192-2025-07-12-0-v1-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`
albertwang8192-2025-07-12-0-v1-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`
albertwang8192-2025-07-12-0-v1-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`
albertwang8192-2025-07-12-0-v1-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`
albertwang8192-2025-07-12-0-v1-mkmlizer: Downloaded to shared memory in 62.297s
albertwang8192-2025-07-12-0-v1-mkmlizer: Checking if AlbertWang8192/2025-07-12_0 already exists in ChaiML
albertwang8192-2025-07-12-0-v1-mkmlizer: Creating repo ChaiML/2025-07-12_0 and uploading /tmp/tmp_fb8ggug to it
albertwang8192-2025-07-12-0-v1-mkmlizer: 
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albertwang8192-2025-07-12-0-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp_fb8ggug, device:0
albertwang8192-2025-07-12-0-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-12-0-v1-mkmlizer: quantized model in 30.264s
albertwang8192-2025-07-12-0-v1-mkmlizer: Processed model AlbertWang8192/2025-07-12_0 in 140.939s
albertwang8192-2025-07-12-0-v1-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-12-0-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-12-0-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-12-0-v1/nvidia
albertwang8192-2025-07-12-0-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-12-0-v1/nvidia/special_tokens_map.json
albertwang8192-2025-07-12-0-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-12-0-v1/nvidia/config.json
albertwang8192-2025-07-12-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-12-0-v1/nvidia/tokenizer_config.json
albertwang8192-2025-07-12-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-12-0-v1/nvidia/tokenizer.json
albertwang8192-2025-07-12-0-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-12-0-v1/nvidia/flywheel_model.0.safetensors
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Job albertwang8192-2025-07-12-0-v1-mkmlizer completed after 167.9s with status: succeeded
Stopping job with name albertwang8192-2025-07-12-0-v1-mkmlizer
Pipeline stage MKMLizer completed in 168.47s
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Running pipeline stage MKMLTemplater
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Running pipeline stage MKMLDeployer
Creating inference service albertwang8192-2025-07-12-0-v1
Waiting for inference service albertwang8192-2025-07-12-0-v1 to be ready
Inference service albertwang8192-2025-07-12-0-v1 ready after 220.8436737060547s
Pipeline stage MKMLDeployer completed in 221.71s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.83031964302063s
Received healthy response to inference request in 1.6261181831359863s
Received healthy response to inference request in 2.136803388595581s
Received healthy response to inference request in 1.812483310699463s
Received healthy response to inference request in 1.509493112564087s
5 requests
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5th percentile: 1.5328181266784668
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mean time: 1.9830435276031495
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