chaiml-kimid-v3-lr5e6g32

developer_uid: zonemercy
submission_id: chaiml-kimid-v3-lr5e6g32_v4
model_name: test
model_group: ChaiML/kimid-v3_lr5e6g32
status: torndown
timestamp: 2025-12-12T18:28:01+00:00
num_battles: 8771
num_wins: 4446
celo_rating: 1292.08
family_friendly_score: 0.5024
family_friendly_standard_error: 0.007070986352695075
submission_type: basic
model_repo: ChaiML/kimid-v3_lr5e6g32
model_architecture: MistralForCausalLM
model_num_parameters: 24096691200.0
best_of: 8
max_input_tokens: 2048
max_output_tokens: 72
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.43975999626476436, 'latency_mean': 2.2738892889022826, 'latency_p50': 2.2767070531845093, 'latency_p90': 2.4761539459228517}, {'batch_size': 2, 'throughput': 0.6637786611995189, 'latency_mean': 3.0076983046531676, 'latency_p50': 3.0183078050613403, 'latency_p90': 3.2525478839874267}, {'batch_size': 3, 'throughput': 0.8159832886906357, 'latency_mean': 3.6606031596660613, 'latency_p50': 3.657852530479431, 'latency_p90': 3.929061698913574}, {'batch_size': 4, 'throughput': 0.9192020492705087, 'latency_mean': 4.346281145811081, 'latency_p50': 4.3289666175842285, 'latency_p90': 4.866451692581177}, {'batch_size': 5, 'throughput': 0.9811768249300749, 'latency_mean': 5.063556092977524, 'latency_p50': 5.083309650421143, 'latency_p90': 5.555153107643127}]
gpu_counts: {'NVIDIA A100-SXM4-80GB': 1}
display_name: test
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: ChaiML/kimid-v3_lr5e6g32
model_size: 24B
ranking_group: single
throughput_3p7s: 0.83
us_pacific_date: 2025-12-06
win_ratio: 0.5068977311595029
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>', 'User:'], 'max_input_tokens': 2048, 'best_of': 8, 'max_output_tokens': 72}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {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-kimid-v3-lr5e6g32-v4-mkmlizer
Waiting for job on chaiml-kimid-v3-lr5e6g32-v4-mkmlizer to finish
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: bash: no job control in this shell
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer:   __import__('pkg_resources').declare_namespace(__name__)
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
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chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
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chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  Version: 0.30.6+torch280                                           ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  belonging to:                                                      ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: Downloaded to shared memory in 36.573s
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: Checking if ChaiML/kimid-v3_lr5e6g32 already exists in ChaiML
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmp1xmqgshy, device:0
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: 
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chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: The tokenizer you are loading from '/tmp/tmp1xmqgshy' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: quantized model in 276.438s
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: Processed model ChaiML/kimid-v3_lr5e6g32 in 313.012s
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: creating bucket guanaco-mkml-models
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia/config.json
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia/special_tokens_map.json
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia/tokenizer_config.json
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia/tokenizer.json
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia/flywheel_model.1.safetensors
chaiml-kimid-v3-lr5e6g32-v4-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-kimid-v3-lr5e6g32-v4/nvidia/flywheel_model.0.safetensors
Job chaiml-kimid-v3-lr5e6g32-v4-mkmlizer completed after 358.21s with status: succeeded
Stopping job with name chaiml-kimid-v3-lr5e6g32-v4-mkmlizer
Pipeline stage MKMLizer completed in 358.70s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.15s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-kimid-v3-lr5e6g32-v4
Waiting for inference service chaiml-kimid-v3-lr5e6g32-v4 to be ready
Inference service chaiml-kimid-v3-lr5e6g32-v4 ready after 190.82335138320923s
Pipeline stage MKMLDeployer completed in 191.39s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.7630507946014404s
Received healthy response to inference request in 2.4352245330810547s
Received healthy response to inference request in 2.254819393157959s
Received healthy response to inference request in 2.4484052658081055s
Received healthy response to inference request in 2.5866849422454834s
5 requests
0 failed requests
5th percentile: 2.2909004211425783
10th percentile: 2.326981449127197
20th percentile: 2.3991435050964354
30th percentile: 2.437860679626465
40th percentile: 2.4431329727172852
50th percentile: 2.4484052658081055
60th percentile: 2.503717136383057
70th percentile: 2.5590290069580077
80th percentile: 2.621958112716675
90th percentile: 2.6925044536590574
95th percentile: 2.727777624130249
99th percentile: 2.7559961605072023
mean time: 2.4976369857788088
Pipeline stage StressChecker completed in 14.03s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.97s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 0.63s
Shutdown handler de-registered
chaiml-kimid-v3-lr5e6g32_v4 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Generating Leaderboard row for %s
Generated Leaderboard row for %s
Pipeline stage OfflineFamilyFriendlyScorer completed in 2641.68s
Shutdown handler de-registered
chaiml-kimid-v3-lr5e6g32_v4 status is now torndown due to DeploymentManager action