chaiml-1106-quang-ir-mi_63631

developer_uid: chai_backend_admin

submission_id: chaiml-1106-quang-ir-mi_63631_v1

model_name: training123

model_group: ChaiML/1106-quang-ir-mix

status: torndown

timestamp: 2025-11-10T08:36:44+00:00

num_battles: 5278

num_wins: 2587

celo_rating: 1290.16

family_friendly_score: 0.5820000000000001

family_friendly_standard_error: 0.006975327949279518

submission_type: basic

model_repo: ChaiML/1106-quang-ir-mixall-cld-i8a8-hl-mult-sth-f25000-dpo_0164641ep_2e6ct

model_architecture: MistralForCausalLM

model_num_parameters: 24096691200.0

best_of: 8

max_input_tokens: 2048

max_output_tokens: 64

reward_model: default

latencies: [{'batch_size': 1, 'throughput': 0.38013215514736487, 'latency_mean': 2.630538569688797, 'latency_p50': 2.6155515909194946, 'latency_p90': 2.9025809526443482}, {'batch_size': 2, 'throughput': 0.5696720983947825, 'latency_mean': 3.5086862063407898, 'latency_p50': 3.525964140892029, 'latency_p90': 3.8138623237609863}, {'batch_size': 3, 'throughput': 0.6996553782270222, 'latency_mean': 4.269089291095733, 'latency_p50': 4.271103858947754, 'latency_p90': 4.594951725006103}, {'batch_size': 4, 'throughput': 0.7914225157438055, 'latency_mean': 5.026824824810028, 'latency_p50': 5.0390084981918335, 'latency_p90': 5.599424982070922}, {'batch_size': 5, 'throughput': 0.8597814757477048, 'latency_mean': 5.8017679929733275, 'latency_p50': 5.766677618026733, 'latency_p90': 6.572088408470154}]

gpu_counts: {'NVIDIA L40S': 1}

display_name: training123

is_internal_developer: True

language_model: ChaiML/1106-quang-ir-mixall-cld-i8a8-hl-mult-sth-f25000-dpo_0164641ep_2e6ct

model_size: 24B

ranking_group: single

throughput_3p7s: 0.61

us_pacific_date: 2025-11-07

win_ratio: 0.49014778325123154

generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['You:', '</s>', '####', '\n'], 'max_input_tokens': 2048, 'best_of': 8, 'max_output_tokens': 64}

formatter: {'memory_template': "{bot_name}'s persona: {memory}", 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': 'You: {message}\n', 'response_template': '####\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
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Running pipeline stage MKMLizer
Starting job with name chaiml-1106-quang-ir-mi-63631-v1-mkmlizer
Waiting for job on chaiml-1106-quang-ir-mi-63631-v1-mkmlizer to finish
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║                                                                     ║
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chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║                                                                     ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  Version: 0.30.2                                                    ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║                                                                     ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  belonging to:                                                      ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║                                                                     ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ║                                                                     ║
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: Downloaded to shared memory in 63.228s
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: Checking if ChaiML/1106-quang-ir-mixall-cld-i8a8-hl-mult-sth-f25000-dpo_0164641ep_2e6ct already exists in ChaiML
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpwyjnxm01, device:0
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: quantized model in 42.980s
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: Processed model ChaiML/1106-quang-ir-mixall-cld-i8a8-hl-mult-sth-f25000-dpo_0164641ep_2e6ct in 106.208s
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: creating bucket guanaco-mkml-models
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia/config.json
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia/special_tokens_map.json
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia/tokenizer_config.json
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia/tokenizer.json
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia/flywheel_model.1.safetensors
chaiml-1106-quang-ir-mi-63631-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-1106-quang-ir-mi-63631-v1/nvidia/flywheel_model.0.safetensors
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Job chaiml-1106-quang-ir-mi-63631-v1-mkmlizer completed after 174.92s with status: succeeded
Stopping job with name chaiml-1106-quang-ir-mi-63631-v1-mkmlizer
Pipeline stage MKMLizer completed in 175.42s
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Creating inference service chaiml-1106-quang-ir-mi-63631-v1
Waiting for inference service chaiml-1106-quang-ir-mi-63631-v1 to be ready
Failed to get response for submission chaiml-iterative-rm-pa_66559_v11: HTTPConnectionPool(host='chaiml-iterative-rm-pa-66559-v11-predictor.tenant-chaiml-guanaco.kchai-coreweave-us-east-04a.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
Inference service chaiml-1106-quang-ir-mi-63631-v1 ready after 160.5968782901764s
Pipeline stage MKMLDeployer completed in 161.15s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.336754322052002s
Received healthy response to inference request in 2.237140417098999s
Received healthy response to inference request in 2.6390743255615234s
Received healthy response to inference request in 2.1384732723236084s
Received healthy response to inference request in 2.073474645614624s
5 requests
0 failed requests
5th percentile: 2.086474370956421
10th percentile: 2.0994740962982177
20th percentile: 2.1254735469818113
30th percentile: 2.1582067012786865
40th percentile: 2.1976735591888428
50th percentile: 2.237140417098999
60th percentile: 2.2769859790802003
70th percentile: 2.3168315410614015
80th percentile: 2.3972183227539063
90th percentile: 2.5181463241577147
95th percentile: 2.578610324859619
99th percentile: 2.6269815254211424
mean time: 2.2849833965301514
Pipeline stage StressChecker completed in 12.69s
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Pipeline stage OfflineFamilyFriendlyScorer completed in 2985.88s
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chaiml-1106-quang-ir-mi_63631_v1 status is now inactive due to auto deactivation removed underperforming models
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