developer_uid: Jellywibble
submission_id: mistralai-mistral-nemo_9330_v200
model_name: lkjlkj
model_group: mistralai/Mistral-Nemo-I
status: inactive
timestamp: 2024-11-23T22:30:20+00:00
num_battles: 19555
num_wins: 9378
celo_rating: 1245.76
family_friendly_score: 0.5760000000000001
family_friendly_standard_error: 0.0069889054937092975
submission_type: basic
model_repo: mistralai/Mistral-Nemo-Instruct-2407
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
latencies: [{'batch_size': 1, 'throughput': 0.6090932390198692, 'latency_mean': 1.6417155981063842, 'latency_p50': 1.6379919052124023, 'latency_p90': 1.8009688138961792}, {'batch_size': 3, 'throughput': 1.1226090423123947, 'latency_mean': 2.6620065474510195, 'latency_p50': 2.66944682598114, 'latency_p90': 2.9449450731277467}, {'batch_size': 5, 'throughput': 1.3713347463847168, 'latency_mean': 3.625499038696289, 'latency_p50': 3.631030321121216, 'latency_p90': 4.109947443008423}, {'batch_size': 6, 'throughput': 1.4414312095430277, 'latency_mean': 4.139336508512497, 'latency_p50': 4.115864992141724, 'latency_p90': 4.674829411506653}, {'batch_size': 8, 'throughput': 1.4966216838726674, 'latency_mean': 5.317642998695374, 'latency_p50': 5.3876965045928955, 'latency_p90': 5.952361226081848}, {'batch_size': 10, 'throughput': 1.5384837751950342, 'latency_mean': 6.455522904396057, 'latency_p50': 6.524429559707642, 'latency_p90': 7.260169434547424}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: lkjlkj
is_internal_developer: True
language_model: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
ranking_group: single
throughput_3p7s: 1.39
us_pacific_date: 2024-11-23
win_ratio: 0.479570442342112
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'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{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 mistralai-mistral-nemo-9330-v200-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v200-mkmlizer to finish
mistralai-mistral-nemo-9330-v200-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v200-mkmlizer: ║     _____            __           __                                ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║       /___/                                                         ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  Version: 0.11.12                                                   ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  https://mk1.ai                                                     ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  belonging to:                                                      ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v200-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
mistralai-mistral-nemo-9330-v200-mkmlizer: Downloaded to shared memory in 51.902s
mistralai-mistral-nemo-9330-v200-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpx2tx5m7b, device:0
mistralai-mistral-nemo-9330-v200-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v200-mkmlizer: quantized model in 36.134s
mistralai-mistral-nemo-9330-v200-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 88.037s
mistralai-mistral-nemo-9330-v200-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v200-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v200-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v200
mistralai-mistral-nemo-9330-v200-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v200/special_tokens_map.json
mistralai-mistral-nemo-9330-v200-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v200/config.json
mistralai-mistral-nemo-9330-v200-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v200/tokenizer_config.json
mistralai-mistral-nemo-9330-v200-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v200/tokenizer.json
mistralai-mistral-nemo-9330-v200-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v200/flywheel_model.0.safetensors
mistralai-mistral-nemo-9330-v200-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:11, 30.94it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:06, 52.39it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:07, 44.33it/s]
Loading 0:   7%|▋         | 24/363 [00:00<00:08, 42.33it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:06, 48.21it/s]
Loading 0:  10%|█         | 37/363 [00:00<00:07, 42.01it/s]
Loading 0:  12%|█▏        | 42/363 [00:01<00:08, 39.25it/s]
Loading 0:  13%|█▎        | 48/363 [00:01<00:07, 42.94it/s]
Loading 0:  15%|█▍        | 53/363 [00:01<00:07, 41.43it/s]
Loading 0:  16%|█▌        | 58/363 [00:01<00:07, 43.18it/s]
Loading 0:  17%|█▋        | 63/363 [00:01<00:09, 30.98it/s]
Loading 0:  19%|█▊        | 68/363 [00:01<00:08, 34.68it/s]
Loading 0:  20%|██        | 73/363 [00:01<00:09, 31.49it/s]
Loading 0:  22%|██▏       | 81/363 [00:02<00:07, 40.02it/s]
Loading 0:  24%|██▍       | 87/363 [00:02<00:06, 40.13it/s]
Loading 0:  25%|██▌       | 92/363 [00:02<00:06, 40.60it/s]
Loading 0:  27%|██▋       | 99/363 [00:02<00:05, 45.80it/s]
Loading 0:  29%|██▉       | 105/363 [00:02<00:05, 44.13it/s]
Loading 0:  31%|███       | 112/363 [00:02<00:05, 48.17it/s]
Loading 0:  32%|███▏      | 117/363 [00:02<00:05, 43.84it/s]
Loading 0:  34%|███▎      | 122/363 [00:02<00:05, 44.35it/s]
Loading 0:  35%|███▍      | 127/363 [00:03<00:06, 37.38it/s]
Loading 0:  37%|███▋      | 134/363 [00:03<00:05, 44.31it/s]
Loading 0:  38%|███▊      | 139/363 [00:03<00:05, 43.63it/s]
Loading 0:  40%|███▉      | 144/363 [00:03<00:07, 28.52it/s]
Loading 0:  41%|████      | 149/363 [00:03<00:07, 30.26it/s]
Loading 0:  43%|████▎     | 156/363 [00:03<00:05, 37.54it/s]
Loading 0:  44%|████▍     | 161/363 [00:04<00:05, 39.88it/s]
Loading 0:  46%|████▌     | 166/363 [00:04<00:04, 41.78it/s]
Loading 0:  47%|████▋     | 172/363 [00:04<00:04, 41.59it/s]
Loading 0:  49%|████▉     | 177/363 [00:04<00:04, 39.29it/s]
Loading 0:  51%|█████     | 184/363 [00:04<00:04, 44.58it/s]
Loading 0:  52%|█████▏    | 190/363 [00:04<00:03, 44.12it/s]
Loading 0:  54%|█████▎    | 195/363 [00:04<00:03, 43.41it/s]
Loading 0:  56%|█████▌    | 202/363 [00:04<00:03, 47.98it/s]
Loading 0:  57%|█████▋    | 208/363 [00:05<00:03, 46.35it/s]
Loading 0:  59%|█████▊    | 213/363 [00:05<00:03, 43.89it/s]
Loading 0:  60%|██████    | 219/363 [00:05<00:03, 47.83it/s]
Loading 0:  62%|██████▏   | 224/363 [00:05<00:04, 34.62it/s]
Loading 0:  63%|██████▎   | 229/363 [00:05<00:03, 35.07it/s]
Loading 0:  64%|██████▍   | 233/363 [00:05<00:03, 35.87it/s]
Loading 0:  66%|██████▌   | 238/363 [00:05<00:03, 38.30it/s]
Loading 0:  67%|██████▋   | 244/363 [00:06<00:03, 39.55it/s]
Loading 0:  69%|██████▊   | 249/363 [00:06<00:02, 39.72it/s]
Loading 0:  71%|███████   | 256/363 [00:06<00:02, 45.06it/s]
Loading 0:  72%|███████▏  | 262/363 [00:06<00:02, 44.04it/s]
Loading 0:  74%|███████▎  | 267/363 [00:06<00:02, 43.97it/s]
Loading 0:  75%|███████▌  | 273/363 [00:06<00:01, 47.85it/s]
Loading 0:  77%|███████▋  | 278/363 [00:06<00:01, 47.54it/s]
Loading 0:  78%|███████▊  | 283/363 [00:06<00:01, 47.91it/s]
Loading 0:  80%|███████▉  | 289/363 [00:07<00:01, 45.99it/s]
Loading 0:  81%|████████  | 294/363 [00:07<00:01, 44.07it/s]
Loading 0:  83%|████████▎ | 301/363 [00:07<00:01, 50.31it/s]
Loading 0:  85%|████████▍ | 307/363 [00:14<00:20,  2.77it/s]
Loading 0:  86%|████████▌ | 312/363 [00:14<00:13,  3.69it/s]
Loading 0:  88%|████████▊ | 320/363 [00:14<00:07,  5.76it/s]
Loading 0:  90%|████████▉ | 326/363 [00:14<00:04,  7.66it/s]
Loading 0:  91%|█████████ | 331/363 [00:14<00:03,  9.66it/s]
Loading 0:  93%|█████████▎| 338/363 [00:14<00:01, 13.57it/s]
Loading 0:  95%|█████████▍| 344/363 [00:14<00:01, 17.00it/s]
Loading 0:  96%|█████████▌| 349/363 [00:14<00:00, 20.14it/s]
Loading 0:  98%|█████████▊| 356/363 [00:15<00:00, 26.16it/s]
Loading 0: 100%|█████████▉| 362/363 [00:15<00:00, 29.32it/s]
                                                            

Job mistralai-mistral-nemo-9330-v200-mkmlizer completed after 114.15s with status: succeeded
Stopping job with name mistralai-mistral-nemo-9330-v200-mkmlizer
Pipeline stage MKMLizer completed in 114.66s
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 mistralai-mistral-nemo-9330-v200
Waiting for inference service mistralai-mistral-nemo-9330-v200 to be ready
Inference service mistralai-mistral-nemo-9330-v200 ready after 100.35215282440186s
Pipeline stage MKMLDeployer completed in 100.90s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.3413197994232178s
Received healthy response to inference request in 2.0591907501220703s
Received healthy response to inference request in 1.7283358573913574s
Received healthy response to inference request in 1.7485365867614746s
Received healthy response to inference request in 1.650843858718872s
5 requests
0 failed requests
5th percentile: 1.6663422584533691
10th percentile: 1.6818406581878662
20th percentile: 1.7128374576568604
30th percentile: 1.7323760032653808
40th percentile: 1.7404562950134277
50th percentile: 1.7485365867614746
60th percentile: 1.872798252105713
70th percentile: 1.997059917449951
80th percentile: 2.1156165599823
90th percentile: 2.228468179702759
95th percentile: 2.2848939895629883
99th percentile: 2.330034637451172
mean time: 1.9056453704833984
Pipeline stage StressChecker completed in 10.88s
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 2.22s
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 2.22s
Shutdown handler de-registered
mistralai-mistral-nemo_9330_v200 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 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service mistralai-mistral-nemo-9330-v200-profiler
Waiting for inference service mistralai-mistral-nemo-9330-v200-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
Pipeline stage OfflineFamilyFriendlyScorer completed in 2763.86s
Shutdown handler de-registered
mistralai-mistral-nemo_9330_v200 status is now inactive due to auto deactivation removed underperforming models