junhua024-chai-16-full-_94000

developer_uid: junhua024

submission_id: junhua024-chai-16-full-_94000_v6

model_name: junhua024-chai-16-full-_94000_v6

model_group: junhua024/chai_16_full_q

status: torndown

timestamp: 2025-07-20T13:18:25+00:00

num_battles: 5679

num_wins: 2747

celo_rating: 1279.22

family_friendly_score: 0.0

family_friendly_standard_error: 0.0

submission_type: basic

model_repo: junhua024/chai_16_full_qkv100_o106_ffn106_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': 0.5935836434662684, 'latency_mean': 1.6845001363754273, 'latency_p50': 1.692439317703247, 'latency_p90': 1.8509712219238281}, {'batch_size': 3, 'throughput': 1.077307992694049, 'latency_mean': 2.7791601073741914, 'latency_p50': 2.789734363555908, 'latency_p90': 3.0123552322387694}, {'batch_size': 5, 'throughput': 1.3019150347027397, 'latency_mean': 3.8175697600841523, 'latency_p50': 3.8284658193588257, 'latency_p90': 4.215579771995545}, {'batch_size': 6, 'throughput': 1.3645421720484918, 'latency_mean': 4.375321437120437, 'latency_p50': 4.3800482749938965, 'latency_p90': 4.915237307548523}, {'batch_size': 8, 'throughput': 1.4317356554193135, 'latency_mean': 5.5322424507141115, 'latency_p50': 5.522671103477478, 'latency_p90': 6.191445612907409}, {'batch_size': 10, 'throughput': 1.45234533004878, 'latency_mean': 6.833956161737442, 'latency_p50': 6.880282998085022, 'latency_p90': 7.684050107002259}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: junhua024-chai-16-full-_94000_v6

is_internal_developer: False

language_model: junhua024/chai_16_full_qkv100_o106_ffn106_1925

model_size: 13B

ranking_group: single

throughput_3p7s: 1.29

us_pacific_date: 2025-07-20

win_ratio: 0.483711921112872

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-94000-v6-mkmlizer
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junhua024-chai-16-full-94000-v6-mkmlizer: ║                                                                     ║
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junhua024-chai-16-full-94000-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-16-full-94000-v6-mkmlizer: ║                                                                     ║
junhua024-chai-16-full-94000-v6-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-16-full-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-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-94000-v6-mkmlizer: quantized model in 32.184s
junhua024-chai-16-full-94000-v6-mkmlizer: Processed model junhua024/chai_16_full_qkv100_o106_ffn106_1925 in 143.195s
junhua024-chai-16-full-94000-v6-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-16-full-94000-v6-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-16-full-94000-v6-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v6/nvidia
junhua024-chai-16-full-94000-v6-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v6/nvidia/config.json
junhua024-chai-16-full-94000-v6-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v6/nvidia/special_tokens_map.json
junhua024-chai-16-full-94000-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v6/nvidia/tokenizer_config.json
junhua024-chai-16-full-94000-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v6/nvidia/tokenizer.json
junhua024-chai-16-full-94000-v6-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-16-full-94000-v6/nvidia/flywheel_model.0.safetensors
Job junhua024-chai-16-full-94000-v6-mkmlizer completed after 171.34s with status: succeeded
Stopping job with name junhua024-chai-16-full-94000-v6-mkmlizer
Pipeline stage MKMLizer completed in 171.86s
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Pipeline stage MKMLTemplater completed in 0.15s
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Creating inference service junhua024-chai-16-full-94000-v6
Waiting for inference service junhua024-chai-16-full-94000-v6 to be ready
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-gy-exp196-sft-gy_92883_v1: HTTPConnectionPool(host='chaiml-gy-exp196-sft-gy-92883-v1-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-94000-v6 ready after 332.9437129497528s
Pipeline stage MKMLDeployer completed in 333.74s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.711946487426758s
Received healthy response to inference request in 1.7146661281585693s
Received healthy response to inference request in 1.6236674785614014s
Received healthy response to inference request in 1.7276642322540283s
Received healthy response to inference request in 1.84248685836792s
5 requests
0 failed requests
5th percentile: 1.641867208480835
10th percentile: 1.6600669384002686
20th percentile: 1.6964663982391357
30th percentile: 1.717265748977661
40th percentile: 1.7224649906158447
50th percentile: 1.7276642322540283
60th percentile: 1.773593282699585
70th percentile: 1.8195223331451416
80th percentile: 2.016378784179688
90th percentile: 2.364162635803223
95th percentile: 2.53805456161499
99th percentile: 2.677168102264404
mean time: 1.9240862369537353
Pipeline stage StressChecker completed in 11.32s
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