submission_id: cycy233-nemo-p-v4-c1_v2
developer_uid: shiroe40
best_of: 8
celo_rating: 1242.24
display_name: auto
family_friendly_score: 0.5712751677852349
family_friendly_standard_error: 0.008085262288272355
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}
generation_params: {'temperature': 1.0, 'top_p': 0.9, 'min_p': 0.05, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['</s>', '###'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: cycy233/nemo-p-v4-c1
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: cycy233/nemo-p-v4-c1
model_name: auto
model_num_parameters: 12772070400.0
model_repo: cycy233/nemo-p-v4-c1
model_size: 13B
num_battles: 3847
num_wins: 1862
ranking_group: single
status: inactive
submission_type: basic
timestamp: 2024-09-27T10:35:12+00:00
us_pacific_date: 2024-09-27
win_ratio: 0.4840135170262542
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name cycy233-nemo-p-v4-c1-v2-mkmlizer
Waiting for job on cycy233-nemo-p-v4-c1-v2-mkmlizer to finish
cycy233-nemo-p-v4-c1-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ _____ __ __ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ /___/ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ Version: 0.11.12 ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ https://mk1.ai ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ belonging to: ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ Chai Research Corp. ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-nemo-p-v4-c1-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ _____ __ __ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ /___/ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ Version: 0.11.12 ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ https://mk1.ai ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ belonging to: ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ Chai Research Corp. ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-nemo-p-v4-c1-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-nemo-p-v4-c1-v1-mkmlizer: Downloaded to shared memory in 52.729s
cycy233-nemo-p-v4-c1-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmptxnvf8lu, device:0
cycy233-nemo-p-v4-c1-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cycy233-nemo-p-v4-c1-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py:55: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
cycy233-nemo-p-v4-c1-v1-mkmlizer: tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
cycy233-nemo-p-v4-c1-v2-mkmlizer: Downloaded to shared memory in 49.914s
cycy233-nemo-p-v4-c1-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp8583t_km, device:0
cycy233-nemo-p-v4-c1-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cycy233-nemo-p-v4-c1-v2-mkmlizer: /opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py:55: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
cycy233-nemo-p-v4-c1-v2-mkmlizer: tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
cycy233-nemo-p-v4-c1-v1-mkmlizer: quantized model in 36.287s
cycy233-nemo-p-v4-c1-v1-mkmlizer: Processed model cycy233/nemo-p-v4-c1 in 89.016s
cycy233-nemo-p-v4-c1-v1-mkmlizer: creating bucket guanaco-mkml-models
cycy233-nemo-p-v4-c1-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-nemo-p-v4-c1-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v1
cycy233-nemo-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v1/config.json
cycy233-nemo-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v1/special_tokens_map.json
cycy233-nemo-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v1/tokenizer_config.json
cycy233-nemo-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v1/tokenizer.json
cycy233-nemo-p-v4-c1-v2-mkmlizer: quantized model in 42.182s
cycy233-nemo-p-v4-c1-v2-mkmlizer: Processed model cycy233/nemo-p-v4-c1 in 92.096s
cycy233-nemo-p-v4-c1-v2-mkmlizer: creating bucket guanaco-mkml-models
cycy233-nemo-p-v4-c1-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-nemo-p-v4-c1-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v2
cycy233-nemo-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v2/special_tokens_map.json
cycy233-nemo-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v2/config.json
cycy233-nemo-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v2/tokenizer_config.json
cycy233-nemo-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v2/tokenizer.json
cycy233-nemo-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v1/flywheel_model.0.safetensors
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Job cycy233-nemo-p-v4-c1-v1-mkmlizer completed after 113.64s with status: succeeded
Stopping job with name cycy233-nemo-p-v4-c1-v1-mkmlizer
Pipeline stage MKMLizer completed in 113.96s
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Pipeline stage MKMLTemplater completed in 0.17s
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Creating inference service cycy233-nemo-p-v4-c1-v1
Waiting for inference service cycy233-nemo-p-v4-c1-v1 to be ready
cycy233-nemo-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cycy233-nemo-p-v4-c1-v2/flywheel_model.0.safetensors
cycy233-nemo-p-v4-c1-v2-mkmlizer: Loading 0: 0%| | 0/363 [00:00<?, ?it/s] Loading 0: 1%| | 4/363 [00:00<00:09, 36.72it/s] Loading 0: 4%|▎ | 13/363 [00:00<00:05, 66.88it/s] Loading 0: 6%|▌ | 22/363 [00:00<00:04, 77.05it/s] Loading 0: 9%|▊ | 31/363 [00:00<00:04, 82.01it/s] Loading 0: 12%|█▏ | 43/363 [00:00<00:03, 81.80it/s] Loading 0: 15%|█▍ | 53/363 [00:00<00:03, 86.30it/s] Loading 0: 17%|█▋ | 62/363 [00:01<00:13, 22.70it/s] Loading 0: 20%|█▉ | 71/363 [00:01<00:09, 29.44it/s] Loading 0: 22%|██▏ | 79/363 [00:01<00:08, 35.12it/s] Loading 0: 24%|██▍ | 88/363 [00:02<00:06, 42.93it/s] Loading 0: 27%|██▋ | 98/363 [00:02<00:05, 52.87it/s] Loading 0: 31%|███ | 112/363 [00:02<00:03, 64.09it/s] Loading 0: 33%|███▎ | 121/363 [00:02<00:03, 68.97it/s] Loading 0: 36%|███▌ | 130/363 [00:02<00:03, 73.32it/s] Loading 0: 39%|███▉ | 142/363 [00:03<00:09, 22.40it/s] Loading 0: 42%|████▏ | 151/363 [00:03<00:07, 27.99it/s] Loading 0: 44%|████▍ | 160/363 [00:03<00:05, 34.16it/s] Loading 0: 48%|████▊ | 175/363 [00:04<00:04, 46.50it/s] Loading 0: 51%|█████ | 184/363 [00:04<00:03, 52.37it/s] Loading 0: 54%|█████▍ | 196/363 [00:04<00:02, 59.42it/s] Loading 0: 58%|█████▊ | 210/363 [00:04<00:02, 74.54it/s] Loading 0: 61%|██████ | 220/363 [00:04<00:01, 72.27it/s] Loading 0: 63%|██████▎ | 229/363 [00:05<00:06, 21.82it/s] Loading 0: 66%|██████▌ | 238/363 [00:05<00:04, 27.25it/s] Loading 0: 69%|██████▊ | 249/363 [00:06<00:03, 35.78it/s] Loading 0: 71%|███████▏ | 259/363 [00:06<00:02, 41.30it/s] Loading 0: 74%|███████▍ | 268/363 [00:06<00:01, 48.00it/s] Loading 0: 77%|███████▋ | 279/363 [00:06<00:01, 58.67it/s] Loading 0: 79%|███████▉ | 288/363 [00:06<00:01, 64.84it/s] Loading 0: 82%|████████▏ | 297/363 [00:06<00:00, 69.67it/s] Loading 0: 84%|████████▍ | 306/363 [00:07<00:02, 20.78it/s] Loading 0: 86%|████████▌ | 313/363 [00:07<00:01, 25.00it/s] Loading 0: 89%|████████▊ | 322/363 [00:08<00:01, 31.36it/s] Loading 0: 93%|█████████▎| 337/363 [00:08<00:00, 44.30it/s] Loading 0: 96%|█████████▌| 349/363 [00:08<00:00, 51.86it/s] Loading 0: 99%|█████████▊| 358/363 [00:08<00:00, 57.57it/s]
Job cycy233-nemo-p-v4-c1-v2-mkmlizer completed after 123.78s with status: succeeded
Stopping job with name cycy233-nemo-p-v4-c1-v2-mkmlizer
Pipeline stage MKMLizer completed in 124.17s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
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Running pipeline stage MKMLDeployer
Creating inference service cycy233-nemo-p-v4-c1-v2
Waiting for inference service cycy233-nemo-p-v4-c1-v2 to be ready
Inference service cycy233-nemo-p-v4-c1-v1 ready after 230.59575390815735s
Pipeline stage MKMLDeployer completed in 231.00s
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Running pipeline stage StressChecker
Inference service cycy233-nemo-p-v4-c1-v2 ready after 220.47418236732483s
Pipeline stage MKMLDeployer completed in 220.84s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.3795371055603027s
Received healthy response to inference request in 1.8755607604980469s
Received healthy response to inference request in 2.255413770675659s
Received healthy response to inference request in 1.7176649570465088s
Received healthy response to inference request in 2.032214879989624s
Received healthy response to inference request in 1.9333486557006836s
Received healthy response to inference request in 1.7613027095794678s
Received healthy response to inference request in 1.7639877796173096s
5 requests
0 failed requests
5th percentile: 1.726929521560669
10th percentile: 1.736194086074829
Received healthy response to inference request in 1.6951770782470703s
20th percentile: 1.7547232151031493
30th percentile: 1.786302375793457
40th percentile: 1.8309315681457519
50th percentile: 1.8755607604980469
60th percentile: 1.8986759185791016
70th percentile: 1.9217910766601562
80th percentile: 2.0225863456726074
90th percentile: 2.201061725616455
95th percentile: 2.290299415588379
99th percentile: 2.361689567565918
mean time: 1.9340198516845704
Pipeline stage StressChecker completed in 11.23s
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Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
Received healthy response to inference request in 1.7958996295928955s
5 requests
0 failed requests
5th percentile: 1.7084022045135498
10th percentile: 1.7216273307800294
20th percentile: 1.7480775833129882
30th percentile: 1.7682220935821533
40th percentile: 1.7820608615875244
50th percentile: 1.7958996295928955
60th percentile: 1.890425729751587
70th percentile: 1.9849518299102782
80th percentile: 2.0768546581268312
90th percentile: 2.166134214401245
95th percentile: 2.210773992538452
99th percentile: 2.2464858150482176
mean time: 1.9080016136169433
Pipeline stage StressChecker completed in 11.06s
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Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 2.90s
Shutdown handler de-registered
Pipeline stage TriggerMKMLProfilingPipeline completed in 5.19s
cycy233-nemo-p-v4-c1_v2 status is now deployed due to DeploymentManager action
Shutdown handler de-registered
Shutdown handler registered
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.15s
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Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.15s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service cycy233-nemo-p-v4-c1-v2-profiler
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Tearing down inference service cycy233-nemo-p-v4-c1-v2-profiler
%s, retrying in %s seconds...
Creating inference service cycy233-nemo-p-v4-c1-v2-profiler
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Tearing down inference service cycy233-nemo-p-v4-c1-v2-profiler
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Creating inference service cycy233-nemo-p-v4-c1-v2-profiler
Waiting for inference service cycy233-nemo-p-v4-c1-v2-profiler to be ready
Tearing down inference service cycy233-nemo-p-v4-c1-v2-profiler
clean up pipeline due to error=%s
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.15s
Shutdown handler de-registered
cycy233-nemo-p-v4-c1_v2 status is now inactive due to auto deactivation removed underperforming models