albertwang8192-2025-07-11-7

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-11-7_v11

model_name: 2025-07-11_7_v11

model_group: AlbertWang8192/2025-07-1

status: torndown

timestamp: 2025-07-13T17:30:46+00:00

num_battles: 10544

num_wins: 4867

celo_rating: 1258.85

family_friendly_score: 0.5498000000000001

family_friendly_standard_error: 0.007035907333102107

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': 0.5883958262059895, 'latency_mean': 1.699352241754532, 'latency_p50': 1.7115026712417603, 'latency_p90': 1.862547254562378}, {'batch_size': 3, 'throughput': 1.0552952906851607, 'latency_mean': 2.834882748126984, 'latency_p50': 2.8670718669891357, 'latency_p90': 3.161499047279358}, {'batch_size': 5, 'throughput': 1.2542066571618906, 'latency_mean': 3.9710448491573334, 'latency_p50': 4.010480523109436, 'latency_p90': 4.436908292770386}, {'batch_size': 6, 'throughput': 1.321494751707487, 'latency_mean': 4.512253451347351, 'latency_p50': 4.478492259979248, 'latency_p90': 5.0266129016876215}, {'batch_size': 8, 'throughput': 1.3843119048223385, 'latency_mean': 5.7262870001792905, 'latency_p50': 5.737766146659851, 'latency_p90': 6.422651624679565}, {'batch_size': 10, 'throughput': 1.4017635785223082, 'latency_mean': 7.079225174188614, 'latency_p50': 7.056808233261108, 'latency_p90': 8.087538576126098}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-11_7_v11

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: 0.4615895295902883

generation_params: {'temperature': 0.7, 'top_p': 0.98, 'min_p': 0.05, 'top_k': 40, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['<|im_end|>', '\n', '<|im_start|>'], '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
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name albertwang8192-2025-07-11-7-v11-mkmlizer
Waiting for job on albertwang8192-2025-07-11-7-v11-mkmlizer to finish
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albertwang8192-2025-07-11-7-v11-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-11-7-v11-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v11-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-11-7-v11-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-v11-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-v11-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-v11-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-v11-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-v11-mkmlizer: Downloaded to shared memory in 36.037s
albertwang8192-2025-07-11-7-v11-mkmlizer: Checking if AlbertWang8192/2025-07-11_7 already exists in ChaiML
albertwang8192-2025-07-11-7-v11-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpo1n9ny16, device:0
albertwang8192-2025-07-11-7-v11-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-11-7-v11-mkmlizer: quantized model in 36.800s
albertwang8192-2025-07-11-7-v11-mkmlizer: Processed model AlbertWang8192/2025-07-11_7 in 72.925s
albertwang8192-2025-07-11-7-v11-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-11-7-v11-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-11-7-v11-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v11/nvidia
albertwang8192-2025-07-11-7-v11-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v11/nvidia/config.json
albertwang8192-2025-07-11-7-v11-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v11/nvidia/tokenizer.json
albertwang8192-2025-07-11-7-v11-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v11/nvidia/flywheel_model.0.safetensors
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Job albertwang8192-2025-07-11-7-v11-mkmlizer completed after 105.57s with status: succeeded
Stopping job with name albertwang8192-2025-07-11-7-v11-mkmlizer
Pipeline stage MKMLizer completed in 106.04s
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Running pipeline stage MKMLTemplater
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Creating inference service albertwang8192-2025-07-11-7-v11
Waiting for inference service albertwang8192-2025-07-11-7-v11 to be ready
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-v11 ready after 211.00556325912476s
Pipeline stage MKMLDeployer completed in 211.57s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.5013365745544434s
Received healthy response to inference request in 1.7589035034179688s
Received healthy response to inference request in 1.5162713527679443s
Received healthy response to inference request in 1.5611581802368164s
Received healthy response to inference request in 1.716583013534546s
5 requests
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5th percentile: 1.5252487182617187
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90th percentile: 2.2043633460998535
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99th percentile: 2.4716392517089845
mean time: 1.8108505249023437
Pipeline stage StressChecker completed in 10.37s
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