chaiml-1029-quang-ir-ltr_4990

developer_uid: chai_backend_admin

submission_id: chaiml-1029-quang-ir-ltr_4990_v1

model_name: training123

model_group: ChaiML/1029-quang-ir-ltr

status: inactive

timestamp: 2025-10-30T02:10:17+00:00

num_battles: 7347

num_wins: 3813

celo_rating: 1292.74

family_friendly_score: 0.0

family_friendly_standard_error: 0.0

submission_type: basic

model_repo: ChaiML/1029-quang-ir-ltry-mix3-maxb3-cld-adh0-iq7

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': 0.3834407511729436, 'latency_mean': 2.607841292619705, 'latency_p50': 2.584910750389099, 'latency_p90': 2.879681134223938}, {'batch_size': 2, 'throughput': 0.576274767107255, 'latency_mean': 3.4695149517059325, 'latency_p50': 3.4769150018692017, 'latency_p90': 3.7552434682846068}, {'batch_size': 3, 'throughput': 0.710681796284812, 'latency_mean': 4.203289597034455, 'latency_p50': 4.212352991104126, 'latency_p90': 4.5516442298889155}, {'batch_size': 4, 'throughput': 0.8054859202196926, 'latency_mean': 4.949664350748062, 'latency_p50': 4.967818021774292, 'latency_p90': 5.601999807357788}, {'batch_size': 5, 'throughput': 0.8771425543955563, 'latency_mean': 5.6770866024494175, 'latency_p50': 5.657897353172302, 'latency_p90': 6.411368060111999}]

gpu_counts: {'NVIDIA L40S': 1}

display_name: training123

is_internal_developer: True

language_model: ChaiML/1029-quang-ir-ltry-mix3-maxb3-cld-adh0-iq7

model_size: 24B

ranking_group: single

throughput_3p7s: 0.63

us_pacific_date: 2025-10-29

win_ratio: 0.5189873417721519

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': ['####\n', '</s>', '\n', 'You:', '####'], '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
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer
Waiting for job on chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer to finish
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║                                                                     ║
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chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║                                                                     ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  Version: 0.30.2                                                    ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║                                                                     ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  belonging to:                                                      ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║                                                                     ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ║                                                                     ║
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: Downloaded to shared memory in 65.390s
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: Checking if ChaiML/1029-quang-ir-ltry-mix3-maxb3-cld-adh0-iq7 already exists in ChaiML
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpy5qeuexy, device:0
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: quantized model in 41.814s
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: Processed model ChaiML/1029-quang-ir-ltry-mix3-maxb3-cld-adh0-iq7 in 107.204s
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: creating bucket guanaco-mkml-models
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia/config.json
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia/special_tokens_map.json
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia/tokenizer_config.json
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia/tokenizer.json
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia/flywheel_model.1.safetensors
chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-1029-quang-ir-ltr-4990-v1/nvidia/flywheel_model.0.safetensors
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Job chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer completed after 208.38s with status: succeeded
Stopping job with name chaiml-1029-quang-ir-ltr-4990-v1-mkmlizer
Pipeline stage MKMLizer completed in 211.54s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.23s
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Running pipeline stage MKMLDeployer
Creating inference service chaiml-1029-quang-ir-ltr-4990-v1
Waiting for inference service chaiml-1029-quang-ir-ltr-4990-v1 to be ready
Failed to get response for submission chaiml-rirv938-mistral_56339_v14: ('http://guanaco-model-mesh-load-balancer.model-mesh.k2.chaiverse.com/models/chaiml-rirv938-mistral_56339_v14/predict', '{"detail":"503, message=\'Attempt to decode JSON with unexpected mimetype: text/plain\', url=\'http://10.7.129.201:8080/models/chaiml-rirv938-mistral_56339_v14/predict\'"}')
Inference service chaiml-1029-quang-ir-ltr-4990-v1 ready after 160.87141394615173s
Pipeline stage MKMLDeployer completed in 161.56s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.7565805912017822s
Received healthy response to inference request in 2.7078752517700195s
Received healthy response to inference request in 2.6607131958007812s
Received healthy response to inference request in 2.4874658584594727s
Received healthy response to inference request in 2.6390583515167236s
5 requests
0 failed requests
5th percentile: 2.517784357070923
10th percentile: 2.548102855682373
20th percentile: 2.6087398529052734
30th percentile: 2.6433893203735352
40th percentile: 2.652051258087158
50th percentile: 2.6607131958007812
60th percentile: 2.6795780181884767
70th percentile: 2.698442840576172
80th percentile: 2.717616319656372
90th percentile: 2.737098455429077
95th percentile: 2.7468395233154297
99th percentile: 2.7546323776245116
mean time: 2.650338649749756
Pipeline stage StressChecker completed in 15.58s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 1.11s
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Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
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