developer_uid: zonemercy
submission_id: chaiml-kimid-v1-cosine_v15
model_name: test
model_group: ChaiML/kimid-v1_cosine
status: inactive
timestamp: 2025-12-04T15:50:55+00:00
num_battles: 34835
num_wins: 17671
celo_rating: 1298.76
family_friendly_score: 0.49839999999999995
family_friendly_standard_error: 0.007071031607905596
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': 0.42485140213938777, 'latency_mean': 2.3536876118183137, 'latency_p50': 2.3706657886505127, 'latency_p90': 2.5529242753982544}, {'batch_size': 2, 'throughput': 0.6333266317917731, 'latency_mean': 3.1548128271102907, 'latency_p50': 3.144827723503113, 'latency_p90': 3.3835891008377077}, {'batch_size': 3, 'throughput': 0.7710591246030514, 'latency_mean': 3.8817373490333558, 'latency_p50': 3.876690149307251, 'latency_p90': 4.434495854377746}, {'batch_size': 4, 'throughput': 0.871632514230432, 'latency_mean': 4.5736865496635435, 'latency_p50': 4.5875831842422485, 'latency_p90': 5.084229063987732}, {'batch_size': 5, 'throughput': 0.9295131789786678, 'latency_mean': 5.368165653944016, 'latency_p50': 5.366176605224609, 'latency_p90': 6.049511480331421}]
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: 0.74
us_pacific_date: 2025-12-04
win_ratio: 0.5072771637720683
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-v15-mkmlizer
Waiting for job on chaiml-kimid-v1-cosine-v15-mkmlizer to finish
chaiml-kimid-v1-cosine-v15-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-kimid-v1-cosine-v15-mkmlizer: bash: no job control in this shell
chaiml-kimid-v1-cosine-v15-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-v15-mkmlizer:   __import__('pkg_resources').declare_namespace(__name__)
chaiml-kimid-v1-cosine-v15-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-kimid-v1-cosine-v15-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  Version: 0.30.6+torch280                                           ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  belonging to:                                                      ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v15-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-kimid-v1-cosine-v15-mkmlizer: Downloaded to shared memory in 46.224s
chaiml-kimid-v1-cosine-v15-mkmlizer: Checking if ChaiML/kimid-v1_cosine already exists in ChaiML
chaiml-kimid-v1-cosine-v15-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmp9hcbfm3x, device:0
chaiml-kimid-v1-cosine-v15-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-kimid-v1-cosine-v15-mkmlizer: 
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chaiml-kimid-v1-cosine-v15-mkmlizer: The tokenizer you are loading from '/tmp/tmp9hcbfm3x' 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-v15-mkmlizer: quantized model in 276.345s
chaiml-kimid-v1-cosine-v15-mkmlizer: Processed model ChaiML/kimid-v1_cosine in 322.570s
chaiml-kimid-v1-cosine-v15-mkmlizer: creating bucket guanaco-mkml-models
chaiml-kimid-v1-cosine-v15-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-kimid-v1-cosine-v15-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia
chaiml-kimid-v1-cosine-v15-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia/config.json
chaiml-kimid-v1-cosine-v15-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia/special_tokens_map.json
chaiml-kimid-v1-cosine-v15-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia/tokenizer_config.json
chaiml-kimid-v1-cosine-v15-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia/tokenizer.json
chaiml-kimid-v1-cosine-v15-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia/flywheel_model.1.safetensors
chaiml-kimid-v1-cosine-v15-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v15/nvidia/flywheel_model.0.safetensors
Job chaiml-kimid-v1-cosine-v15-mkmlizer completed after 367.59s with status: succeeded
Stopping job with name chaiml-kimid-v1-cosine-v15-mkmlizer
Pipeline stage MKMLizer completed in 368.16s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-kimid-v1-cosine-v15
Waiting for inference service chaiml-kimid-v1-cosine-v15 to be ready
Inference service chaiml-kimid-v1-cosine-v15 ready after 181.47005486488342s
Pipeline stage MKMLDeployer completed in 182.13s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.4972825050354004s
Received healthy response to inference request in 2.286552906036377s
Received healthy response to inference request in 2.4915027618408203s
Received healthy response to inference request in 2.2487127780914307s
Received healthy response to inference request in 2.1926472187042236s
5 requests
0 failed requests
5th percentile: 2.203860330581665
10th percentile: 2.2150734424591065
20th percentile: 2.2374996662139894
30th percentile: 2.25628080368042
40th percentile: 2.2714168548583986
50th percentile: 2.286552906036377
60th percentile: 2.3685328483581545
70th percentile: 2.4505127906799316
80th percentile: 2.4926587104797364
90th percentile: 2.494970607757568
95th percentile: 2.4961265563964843
99th percentile: 2.4970513153076173
mean time: 2.3433396339416506
Pipeline stage StressChecker completed in 13.16s
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 1.19s
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 0.70s
Shutdown handler de-registered
chaiml-kimid-v1-cosine_v15 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.09s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service chaiml-kimid-v1-cosine-v15-profiler
Waiting for inference service chaiml-kimid-v1-cosine-v15-profiler to be ready
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
Generating Leaderboard row for %s
Generated Leaderboard row for %s
Pipeline stage OfflineFamilyFriendlyScorer completed in 4443.29s
Shutdown handler de-registered