developer_uid: azuruce
submission_id: mistralai-mistral-nemo_9330_v216
model_name: mistralai-mistral-nemo_9330_v216
model_group: mistralai/Mistral-Nemo-I
status: inactive
timestamp: 2024-12-19T18:45:05+00:00
num_battles: 51401
num_wins: 24005
celo_rating: 1250.61
family_friendly_score: 0.5893999999999999
family_friendly_standard_error: 0.006957120668782452
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': 0.6144874984591312, 'latency_mean': 1.6272820234298706, 'latency_p50': 1.6130387783050537, 'latency_p90': 1.8057018041610717}, {'batch_size': 3, 'throughput': 1.1324821595315537, 'latency_mean': 2.6392172396183016, 'latency_p50': 2.6527035236358643, 'latency_p90': 2.921133017539978}, {'batch_size': 5, 'throughput': 1.3802396633518936, 'latency_mean': 3.599919812679291, 'latency_p50': 3.5872656106948853, 'latency_p90': 4.029568147659302}, {'batch_size': 6, 'throughput': 1.4517518186615532, 'latency_mean': 4.109278779029847, 'latency_p50': 4.105007648468018, 'latency_p90': 4.63198652267456}, {'batch_size': 8, 'throughput': 1.5136778580379107, 'latency_mean': 5.242659239768982, 'latency_p50': 5.1907795667648315, 'latency_p90': 5.942989230155945}, {'batch_size': 10, 'throughput': 1.555798492042368, 'latency_mean': 6.375553656816482, 'latency_p50': 6.425747632980347, 'latency_p90': 7.1475478410720825}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: mistralai-mistral-nemo_9330_v216
is_internal_developer: True
language_model: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
ranking_group: single
throughput_3p7s: 1.4
us_pacific_date: 2024-12-19
win_ratio: 0.46701426042294897
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 100, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>', '####', 'Bot:', 'User:', 'You:', '<|im_end|>', '<|eot_id|>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': '', 'prompt_template': '', '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-v216-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v216-mkmlizer to finish
mistralai-mistral-nemo-9330-v216-mkmlizer: Downloaded to shared memory in 55.105s
mistralai-mistral-nemo-9330-v216-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpf2nggb58, device:0
mistralai-mistral-nemo-9330-v216-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v216-mkmlizer: quantized model in 37.004s
mistralai-mistral-nemo-9330-v216-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 92.109s
mistralai-mistral-nemo-9330-v216-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v216-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v216-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v216
mistralai-mistral-nemo-9330-v216-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v216/config.json
mistralai-mistral-nemo-9330-v216-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v216/special_tokens_map.json
mistralai-mistral-nemo-9330-v216-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v216/tokenizer_config.json
mistralai-mistral-nemo-9330-v216-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v216/tokenizer.json
mistralai-mistral-nemo-9330-v216-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v216/flywheel_model.0.safetensors
mistralai-mistral-nemo-9330-v216-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:11, 31.85it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:06, 53.20it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:06, 49.37it/s]
Loading 0:   7%|▋         | 25/363 [00:00<00:06, 49.21it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:06, 50.38it/s]
Loading 0:  10%|█         | 37/363 [00:00<00:07, 43.25it/s]
Loading 0:  12%|█▏        | 42/363 [00:00<00:07, 41.58it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:06, 47.62it/s]
Loading 0:  15%|█▍        | 54/363 [00:01<00:06, 48.09it/s]
Loading 0:  17%|█▋        | 60/363 [00:01<00:06, 44.17it/s]
Loading 0:  18%|█▊        | 65/363 [00:01<00:09, 31.02it/s]
Loading 0:  20%|█▉        | 72/363 [00:01<00:07, 37.81it/s]
Loading 0:  21%|██        | 77/363 [00:01<00:07, 39.80it/s]
Loading 0:  23%|██▎       | 82/363 [00:02<00:08, 34.26it/s]
Loading 0:  25%|██▍       | 89/363 [00:02<00:06, 40.47it/s]
Loading 0:  26%|██▌       | 94/363 [00:02<00:06, 40.29it/s]
Loading 0:  27%|██▋       | 99/363 [00:02<00:06, 41.02it/s]
Loading 0:  29%|██▊       | 104/363 [00:02<00:06, 42.26it/s]
Loading 0:  30%|███       | 109/363 [00:02<00:05, 43.43it/s]
Loading 0:  31%|███▏      | 114/363 [00:02<00:06, 36.94it/s]
Loading 0:  33%|███▎      | 118/363 [00:02<00:07, 34.81it/s]
Loading 0:  34%|███▍      | 125/363 [00:03<00:05, 41.31it/s]
Loading 0:  36%|███▌      | 130/363 [00:03<00:05, 40.59it/s]
Loading 0:  37%|███▋      | 135/363 [00:03<00:05, 41.32it/s]
Loading 0:  39%|███▊      | 140/363 [00:03<00:05, 42.95it/s]
Loading 0:  40%|███▉      | 145/363 [00:03<00:08, 26.91it/s]
Loading 0:  41%|████      | 149/363 [00:03<00:08, 26.65it/s]
Loading 0:  42%|████▏     | 154/363 [00:03<00:06, 30.99it/s]
Loading 0:  44%|████▎     | 158/363 [00:04<00:06, 29.52it/s]
Loading 0:  45%|████▍     | 163/363 [00:04<00:06, 33.27it/s]
Loading 0:  46%|████▌     | 167/363 [00:04<00:06, 31.26it/s]
Loading 0:  48%|████▊     | 174/363 [00:04<00:05, 37.58it/s]
Loading 0:  49%|████▉     | 179/363 [00:04<00:04, 38.58it/s]
Loading 0:  51%|█████     | 184/363 [00:04<00:04, 40.18it/s]
Loading 0:  52%|█████▏    | 189/363 [00:04<00:04, 42.47it/s]
Loading 0:  53%|█████▎    | 194/363 [00:05<00:05, 33.28it/s]
Loading 0:  55%|█████▌    | 201/363 [00:05<00:04, 39.31it/s]
Loading 0:  57%|█████▋    | 206/363 [00:05<00:03, 39.93it/s]
Loading 0:  58%|█████▊    | 211/363 [00:05<00:03, 39.85it/s]
Loading 0:  60%|█████▉    | 216/363 [00:05<00:03, 41.38it/s]
Loading 0:  61%|██████    | 221/363 [00:05<00:03, 43.33it/s]
Loading 0:  62%|██████▏   | 226/363 [00:06<00:05, 27.26it/s]
Loading 0:  63%|██████▎   | 230/363 [00:06<00:04, 27.15it/s]
Loading 0:  65%|██████▌   | 237/363 [00:06<00:03, 35.02it/s]
Loading 0:  67%|██████▋   | 242/363 [00:06<00:03, 35.61it/s]
Loading 0:  68%|██████▊   | 247/363 [00:06<00:03, 37.15it/s]
Loading 0:  69%|██████▉   | 252/363 [00:06<00:02, 38.86it/s]
Loading 0:  71%|███████   | 257/363 [00:06<00:03, 32.88it/s]
Loading 0:  73%|███████▎  | 264/363 [00:06<00:02, 39.40it/s]
Loading 0:  74%|███████▍  | 269/363 [00:07<00:02, 39.56it/s]
Loading 0:  75%|███████▌  | 274/363 [00:07<00:02, 39.34it/s]
Loading 0:  77%|███████▋  | 279/363 [00:07<00:02, 40.15it/s]
Loading 0:  78%|███████▊  | 284/363 [00:07<00:02, 33.33it/s]
Loading 0:  80%|████████  | 291/363 [00:07<00:01, 39.98it/s]
Loading 0:  82%|████████▏ | 296/363 [00:07<00:01, 39.23it/s]
Loading 0:  83%|████████▎ | 301/363 [00:07<00:01, 40.53it/s]
Loading 0:  84%|████████▍ | 306/363 [00:14<00:23,  2.46it/s]
Loading 0:  85%|████████▌ | 309/363 [00:14<00:18,  3.00it/s]
Loading 0:  86%|████████▌ | 312/363 [00:14<00:13,  3.71it/s]
Loading 0:  88%|████████▊ | 320/363 [00:15<00:06,  6.53it/s]
Loading 0:  90%|████████▉ | 325/363 [00:15<00:04,  8.70it/s]
Loading 0:  91%|█████████ | 330/363 [00:15<00:03, 10.74it/s]
Loading 0:  93%|█████████▎| 338/363 [00:15<00:01, 16.19it/s]
Loading 0:  94%|█████████▍| 343/363 [00:15<00:01, 19.41it/s]
Loading 0:  96%|█████████▌| 348/363 [00:15<00:00, 20.55it/s]
Loading 0:  98%|█████████▊| 356/363 [00:15<00:00, 28.19it/s]
Loading 0: 100%|█████████▉| 362/363 [00:16<00:00, 30.65it/s]
                                                            

Job mistralai-mistral-nemo-9330-v216-mkmlizer completed after 124.29s with status: succeeded
Stopping job with name mistralai-mistral-nemo-9330-v216-mkmlizer
Pipeline stage MKMLizer completed in 124.86s
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 mistralai-mistral-nemo-9330-v216
Waiting for inference service mistralai-mistral-nemo-9330-v216 to be ready
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Inference service mistralai-mistral-nemo-9330-v216 ready after 240.83249974250793s
Pipeline stage MKMLDeployer completed in 241.35s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.89332914352417s
Received healthy response to inference request in 1.0874948501586914s
Received healthy response to inference request in 1.0889334678649902s
Received healthy response to inference request in 1.0608093738555908s
Received healthy response to inference request in 1.5634329319000244s
5 requests
0 failed requests
5th percentile: 1.066146469116211
10th percentile: 1.071483564376831
20th percentile: 1.0821577548980712
30th percentile: 1.0877825736999511
40th percentile: 1.0883580207824708
50th percentile: 1.0889334678649902
60th percentile: 1.278733253479004
70th percentile: 1.4685330390930176
80th percentile: 1.6294121742248535
90th percentile: 1.7613706588745117
95th percentile: 1.8273499011993408
99th percentile: 1.880133295059204
mean time: 1.3387999534606934
Pipeline stage StressChecker completed in 7.96s
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 1.99s
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 2.36s
Shutdown handler de-registered
mistralai-mistral-nemo_9330_v216 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 0.10s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.10s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service mistralai-mistral-nemo-9330-v216-profiler
Waiting for inference service mistralai-mistral-nemo-9330-v216-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 3484.24s
Shutdown handler de-registered
mistralai-mistral-nemo_9330_v216 status is now inactive due to auto deactivation removed underperforming models