developer_uid: zmeeks
submission_id: vikhrmodels-vikhr-nemo-_15342_v3
model_name: v-v0307
model_group: Vikhrmodels/Vikhr-Nemo-1
status: torndown
timestamp: 2025-06-28T09:54:42+00:00
num_battles: 8228
num_wins: 3507
celo_rating: 1217.38
family_friendly_score: 0.7642
family_friendly_standard_error: 0.006003305089698508
submission_type: basic
model_repo: Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24
model_architecture: MistralForCausalLM
model_num_parameters: 12772090880.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.6036737219227112, 'latency_mean': 1.656409010887146, 'latency_p50': 1.653098225593567, 'latency_p90': 1.8306514978408814}, {'batch_size': 3, 'throughput': 1.0790360284687368, 'latency_mean': 2.7665200078487397, 'latency_p50': 2.771210551261902, 'latency_p90': 3.0627913951873778}, {'batch_size': 5, 'throughput': 1.2985930401968824, 'latency_mean': 3.829019845724106, 'latency_p50': 3.817114233970642, 'latency_p90': 4.302357769012451}, {'batch_size': 6, 'throughput': 1.3744539606066561, 'latency_mean': 4.3381517422199245, 'latency_p50': 4.310632705688477, 'latency_p90': 4.885785317420959}, {'batch_size': 8, 'throughput': 1.4311262116928691, 'latency_mean': 5.551542756557464, 'latency_p50': 5.539472699165344, 'latency_p90': 6.257120561599732}, {'batch_size': 10, 'throughput': 1.4635993891761379, 'latency_mean': 6.785535404682159, 'latency_p50': 6.788926839828491, 'latency_p90': 7.65432391166687}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: v-v0307
is_internal_developer: False
language_model: Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24
model_size: 13B
ranking_group: single
throughput_3p7s: 1.29
us_pacific_date: 2025-06-28
win_ratio: 0.4262275157997083
generation_params: {'temperature': 0.3, 'top_p': 0.7, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': '### Instruction:\n{memory}\n', 'prompt_template': '### Input:\n{prompt}\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '### Response:\n{bot_name}:', 'truncate_by_message': False}
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 vikhrmodels-vikhr-nemo-15342-v3-mkmlizer
Waiting for job on vikhrmodels-vikhr-nemo-15342-v3-mkmlizer to finish
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║                                                                     ║
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vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║                                                                     ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  Version: 0.29.3                                                    ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  https://mk1.ai                                                     ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║                                                                     ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  belonging to:                                                      ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║                                                                     ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  Chai Research Corp.                                                ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ║                                                                     ║
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Downloaded to shared memory in 166.978s
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Checking if Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24 already exists in ChaiML
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp1wrnj215, device:0
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: quantized model in 30.812s
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Processed model Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24 in 197.870s
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: creating bucket guanaco-mkml-models
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/vikhrmodels-vikhr-nemo-15342-v3
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/vikhrmodels-vikhr-nemo-15342-v3/config.json
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/vikhrmodels-vikhr-nemo-15342-v3/special_tokens_map.json
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/vikhrmodels-vikhr-nemo-15342-v3/tokenizer.json
vikhrmodels-vikhr-nemo-15342-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/vikhrmodels-vikhr-nemo-15342-v3/flywheel_model.0.safetensors
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Job vikhrmodels-vikhr-nemo-15342-v3-mkmlizer completed after 218.47s with status: succeeded
Stopping job with name vikhrmodels-vikhr-nemo-15342-v3-mkmlizer
Pipeline stage MKMLizer completed in 218.95s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
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Running pipeline stage MKMLDeployer
Creating inference service vikhrmodels-vikhr-nemo-15342-v3
Waiting for inference service vikhrmodels-vikhr-nemo-15342-v3 to be ready
Inference service vikhrmodels-vikhr-nemo-15342-v3 ready after 161.3151524066925s
Pipeline stage MKMLDeployer completed in 161.86s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.534792423248291s
Received healthy response to inference request in 1.7160735130310059s
Received healthy response to inference request in 2.4966061115264893s
Received healthy response to inference request in 1.7316720485687256s
Received healthy response to inference request in 1.5133163928985596s
5 requests
0 failed requests
5th percentile: 1.5538678169250488
10th percentile: 1.594419240951538
20th percentile: 1.6755220890045166
30th percentile: 1.7191932201385498
40th percentile: 1.7254326343536377
50th percentile: 1.7316720485687256
60th percentile: 2.037645673751831
70th percentile: 2.3436192989349363
80th percentile: 2.5042433738708496
90th percentile: 2.5195178985595703
95th percentile: 2.5271551609039307
99th percentile: 2.533264970779419
mean time: 1.9984920978546143
Pipeline stage StressChecker completed in 11.36s
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Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
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Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.68s
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Running pipeline stage TriggerMKMLProfilingPipeline
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Pipeline stage TriggerMKMLProfilingPipeline completed in 0.68s
Shutdown handler de-registered
vikhrmodels-vikhr-nemo-_15342_v3 status is now deployed due to DeploymentManager action
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Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 3286.77s
Shutdown handler de-registered
vikhrmodels-vikhr-nemo-_15342_v3 status is now inactive due to auto deactivation removed underperforming models
vikhrmodels-vikhr-nemo-_15342_v3 status is now torndown due to DeploymentManager action