developer_uid: zonemercy
submission_id: chaiml-kimid-v1-cosine_v25
model_name: test
model_group: ChaiML/kimid-v1_cosine
status: inactive
timestamp: 2025-12-05T05:37:14+00:00
num_battles: 17749
num_wins: 9153
celo_rating: 1255.85
family_friendly_score: 0.501
family_friendly_standard_error: 0.00707105366971571
submission_type: basic
model_repo: ChaiML/kimid-v1_cosine
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': 0.429601175832548, 'latency_mean': 2.3276787292957306, 'latency_p50': 2.320615768432617, 'latency_p90': 2.529555892944336}, {'batch_size': 2, 'throughput': 0.6447991024874858, 'latency_mean': 3.094296097755432, 'latency_p50': 3.0832629203796387, 'latency_p90': 3.3722797155380246}, {'batch_size': 3, 'throughput': 0.7926629495560253, 'latency_mean': 3.780322104692459, 'latency_p50': 3.765717387199402, 'latency_p90': 4.135353374481201}, {'batch_size': 4, 'throughput': 0.8937811499723629, 'latency_mean': 4.4684738707542415, 'latency_p50': 4.4833003282547, 'latency_p90': 5.044092750549316}, {'batch_size': 5, 'throughput': 0.9472563576194387, 'latency_mean': 5.2547523415088655, 'latency_p50': 5.250141382217407, 'latency_p90': 5.997330117225647}]
gpu_counts: {'NVIDIA L40S': 1}
display_name: test
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: ChaiML/kimid-v1_cosine
model_size: 24B
ranking_group: single
throughput_3p7s: 0.78
us_pacific_date: 2025-12-04
win_ratio: 0.5156910248464702
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': ['</s>', 'You:', '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-v1-cosine-v25-mkmlizer
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Waiting for job on chaiml-kimid-v1-cosine-v25-mkmlizer to finish
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
chaiml-kimid-v1-cosine-v25-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-kimid-v1-cosine-v25-mkmlizer: bash: no job control in this shell
chaiml-kimid-v1-cosine-v25-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-v1-cosine-v25-mkmlizer:   __import__('pkg_resources').declare_namespace(__name__)
chaiml-kimid-v1-cosine-v25-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-kimid-v1-cosine-v25-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
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chaiml-kimid-v1-cosine-v25-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  Version: 0.30.6+torch280                                           ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  belonging to:                                                      ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v25-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-kimid-v1-cosine-v25-mkmlizer: Downloaded to shared memory in 36.443s
chaiml-kimid-v1-cosine-v25-mkmlizer: Checking if ChaiML/kimid-v1_cosine already exists in ChaiML
chaiml-kimid-v1-cosine-v25-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpmyoi1e_v, device:0
chaiml-kimid-v1-cosine-v25-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-kimid-v1-cosine-v25-mkmlizer: 
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chaiml-kimid-v1-cosine-v25-mkmlizer: The tokenizer you are loading from '/tmp/tmpmyoi1e_v' 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-v1-cosine-v25-mkmlizer: quantized model in 276.291s
chaiml-kimid-v1-cosine-v25-mkmlizer: Processed model ChaiML/kimid-v1_cosine in 312.734s
chaiml-kimid-v1-cosine-v25-mkmlizer: creating bucket guanaco-mkml-models
chaiml-kimid-v1-cosine-v25-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-kimid-v1-cosine-v25-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia
chaiml-kimid-v1-cosine-v25-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia/config.json
chaiml-kimid-v1-cosine-v25-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia/special_tokens_map.json
chaiml-kimid-v1-cosine-v25-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia/tokenizer_config.json
chaiml-kimid-v1-cosine-v25-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia/tokenizer.json
chaiml-kimid-v1-cosine-v25-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia/flywheel_model.1.safetensors
chaiml-kimid-v1-cosine-v25-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v25/nvidia/flywheel_model.0.safetensors
Job chaiml-kimid-v1-cosine-v25-mkmlizer completed after 357.46s with status: succeeded
Stopping job with name chaiml-kimid-v1-cosine-v25-mkmlizer
Pipeline stage MKMLizer completed in 358.81s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.17s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-kimid-v1-cosine-v25
Waiting for inference service chaiml-kimid-v1-cosine-v25 to be ready
Inference service chaiml-kimid-v1-cosine-v25 ready after 191.0271611213684s
Pipeline stage MKMLDeployer completed in 191.64s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.729071855545044s
Received healthy response to inference request in 3.4217867851257324s
Received healthy response to inference request in 2.2446351051330566s
Received healthy response to inference request in 2.085587978363037s
Received healthy response to inference request in 2.1662282943725586s
5 requests
0 failed requests
5th percentile: 2.1017160415649414
10th percentile: 2.1178441047668457
20th percentile: 2.1501002311706543
30th percentile: 2.1819096565246583
40th percentile: 2.2132723808288572
50th percentile: 2.2446351051330566
60th percentile: 2.4384098052978516
70th percentile: 2.6321845054626465
80th percentile: 2.8676148414611817
90th percentile: 3.144700813293457
95th percentile: 3.2832437992095946
99th percentile: 3.394078187942505
mean time: 2.5294620037078857
Pipeline stage StressChecker completed in 14.16s
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 0.75s
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 0.71s
Shutdown handler de-registered
chaiml-kimid-v1-cosine_v25 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 2662.54s
Shutdown handler de-registered
chaiml-kimid-v1-cosine_v25 status is now inactive due to auto deactivation removed underperforming models