developer_uid: cgato
submission_id: cgato-nemo-12b-humanize-_7413_v4
model_name: cgato-nemo-12b-humanize-_7413_v4
model_group: cgato/Nemo-12b-Humanize-
status: inactive
timestamp: 2024-12-15T18:42:35+00:00
num_battles: 15074
num_wins: 7379
celo_rating: 1255.77
family_friendly_score: 0.5722
family_friendly_standard_error: 0.006996958767921961
submission_type: basic
model_repo: cgato/Nemo-12b-Humanize-KTO-Experimental-Latest
model_architecture: MistralForCausalLM
model_num_parameters: 12772111360.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
latencies: [{'batch_size': 1, 'throughput': 0.6166473033501636, 'latency_mean': 1.6215844774246215, 'latency_p50': 1.6130024194717407, 'latency_p90': 1.7914839744567872}, {'batch_size': 3, 'throughput': 1.1332255534902045, 'latency_mean': 2.635958112478256, 'latency_p50': 2.645689845085144, 'latency_p90': 2.9124687194824217}, {'batch_size': 5, 'throughput': 1.3822671019868489, 'latency_mean': 3.5940718698501586, 'latency_p50': 3.612898588180542, 'latency_p90': 3.9806713819503785}, {'batch_size': 6, 'throughput': 1.4532928972055277, 'latency_mean': 4.104315462112427, 'latency_p50': 4.10209047794342, 'latency_p90': 4.631786632537842}, {'batch_size': 8, 'throughput': 1.5263987367371172, 'latency_mean': 5.217940983772277, 'latency_p50': 5.26571524143219, 'latency_p90': 5.8494479894638065}, {'batch_size': 10, 'throughput': 1.5658874293138842, 'latency_mean': 6.329853986501694, 'latency_p50': 6.321353077888489, 'latency_p90': 7.132389760017395}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: cgato-nemo-12b-humanize-_7413_v4
is_internal_developer: False
language_model: cgato/Nemo-12b-Humanize-KTO-Experimental-Latest
model_size: 13B
ranking_group: single
throughput_3p7s: 1.41
us_pacific_date: 2024-12-15
win_ratio: 0.48951837601167575
generation_params: {'temperature': 1.0, 'top_p': 1.0, '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': '<|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\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 cgato-nemo-12b-humanize-7413-v4-mkmlizer
Waiting for job on cgato-nemo-12b-humanize-7413-v4-mkmlizer to finish
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ _____ __ __ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ /___/ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ Version: 0.11.12 ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ https://mk1.ai ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ The license key for the current software has been verified as ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ belonging to: ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ Chai Research Corp. ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ Expiration: 2025-01-15 23:59:59 ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ║ ║
cgato-nemo-12b-humanize-7413-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cgato-nemo-12b-humanize-7413-v4-mkmlizer: Downloaded to shared memory in 49.842s
cgato-nemo-12b-humanize-7413-v4-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp4vwjx33d, device:0
cgato-nemo-12b-humanize-7413-v4-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cgato-nemo-12b-humanize-7413-v4-mkmlizer: quantized model in 38.723s
cgato-nemo-12b-humanize-7413-v4-mkmlizer: Processed model cgato/Nemo-12b-Humanize-KTO-Experimental-Latest in 88.565s
cgato-nemo-12b-humanize-7413-v4-mkmlizer: creating bucket guanaco-mkml-models
cgato-nemo-12b-humanize-7413-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cgato-nemo-12b-humanize-7413-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cgato-nemo-12b-humanize-7413-v4
cgato-nemo-12b-humanize-7413-v4-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cgato-nemo-12b-humanize-7413-v4/config.json
cgato-nemo-12b-humanize-7413-v4-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cgato-nemo-12b-humanize-7413-v4/special_tokens_map.json
cgato-nemo-12b-humanize-7413-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cgato-nemo-12b-humanize-7413-v4/tokenizer_config.json
cgato-nemo-12b-humanize-7413-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cgato-nemo-12b-humanize-7413-v4/tokenizer.json
Retrying (%r) after connection broken by '%r': %s
cgato-nemo-12b-humanize-7413-v4-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cgato-nemo-12b-humanize-7413-v4/flywheel_model.0.safetensors
cgato-nemo-12b-humanize-7413-v4-mkmlizer: Loading 0: 0%| | 0/363 [00:00<?, ?it/s] Loading 0: 1%|▏ | 5/363 [00:00<00:12, 29.73it/s] Loading 0: 4%|▎ | 13/363 [00:00<00:07, 48.60it/s] Loading 0: 5%|▌ | 19/363 [00:00<00:08, 42.85it/s] Loading 0: 7%|▋ | 24/363 [00:00<00:08, 41.44it/s] Loading 0: 9%|▊ | 31/363 [00:00<00:06, 47.85it/s] Loading 0: 10%|▉ | 36/363 [00:00<00:06, 47.45it/s] Loading 0: 11%|█▏ | 41/363 [00:01<00:08, 36.74it/s] Loading 0: 13%|█▎ | 48/363 [00:01<00:07, 43.77it/s] Loading 0: 15%|█▍ | 53/363 [00:01<00:07, 41.61it/s] Loading 0: 16%|█▌ | 58/363 [00:01<00:07, 41.20it/s] Loading 0: 17%|█▋ | 63/363 [00:01<00:11, 25.94it/s] Loading 0: 19%|█▊ | 68/363 [00:01<00:09, 29.87it/s] Loading 0: 20%|█▉ | 72/363 [00:01<00:09, 31.82it/s] Loading 0: 21%|██ | 76/363 [00:02<00:08, 33.46it/s] Loading 0: 22%|██▏ | 81/363 [00:02<00:07, 35.26it/s] Loading 0: 23%|██▎ | 85/363 [00:02<00:08, 34.55it/s] Loading 0: 25%|██▍ | 89/363 [00:02<00:07, 34.98it/s] Loading 0: 26%|██▌ | 93/363 [00:02<00:08, 33.69it/s] Loading 0: 27%|██▋ | 98/363 [00:02<00:07, 37.24it/s] Loading 0: 28%|██▊ | 102/363 [00:02<00:07, 35.08it/s] Loading 0: 29%|██▉ | 106/363 [00:02<00:07, 36.13it/s] Loading 0: 31%|███ | 112/363 [00:03<00:06, 38.64it/s] Loading 0: 32%|███▏ | 116/363 [00:03<00:06, 36.76it/s] Loading 0: 33%|███▎ | 120/363 [00:03<00:06, 35.78it/s] Loading 0: 34%|███▍ | 125/363 [00:03<00:06, 39.37it/s] Loading 0: 36%|███▌ | 130/363 [00:03<00:05, 39.62it/s] Loading 0: 37%|███▋ | 135/363 [00:03<00:05, 40.33it/s] Loading 0: 39%|███▊ | 140/363 [00:03<00:05, 41.25it/s] Loading 0: 40%|███▉ | 145/363 [00:04<00:09, 24.02it/s] Loading 0: 41%|████ | 149/363 [00:04<00:08, 24.88it/s] Loading 0: 43%|████▎ | 156/363 [00:04<00:06, 32.43it/s] Loading 0: 44%|████▍ | 161/363 [00:04<00:06, 33.35it/s] Loading 0: 46%|████▌ | 166/363 [00:04<00:05, 35.29it/s] Loading 0: 47%|████▋ | 170/363 [00:04<00:05, 35.08it/s] Loading 0: 48%|████▊ | 174/363 [00:04<00:05, 31.97it/s] Loading 0: 49%|████▉ | 178/363 [00:05<00:05, 31.27it/s] Loading 0: 50%|█████ | 183/363 [00:05<00:05, 35.10it/s] Loading 0: 52%|█████▏ | 187/363 [00:05<00:05, 34.96it/s] Loading 0: 53%|█████▎ | 193/363 [00:05<00:04, 39.64it/s] Loading 0: 55%|█████▍ | 199/363 [00:05<00:04, 39.79it/s] Loading 0: 56%|█████▌ | 204/363 [00:05<00:03, 40.52it/s] Loading 0: 58%|█████▊ | 210/363 [00:05<00:03, 45.24it/s] Loading 0: 59%|█████▉ | 215/363 [00:05<00:03, 44.93it/s] Loading 0: 61%|██████ | 221/363 [00:05<00:02, 48.68it/s] Loading 0: 62%|██████▏ | 226/363 [00:06<00:04, 29.07it/s] Loading 0: 63%|██████▎ | 230/363 [00:06<00:04, 29.33it/s] Loading 0: 65%|██████▌ | 237/363 [00:06<00:03, 36.76it/s] Loading 0: 67%|██████▋ | 242/363 [00:06<00:03, 37.76it/s] Loading 0: 68%|██████▊ | 247/363 [00:06<00:02, 38.95it/s] Loading 0: 69%|██████▉ | 252/363 [00:06<00:02, 40.79it/s] Loading 0: 71%|███████ | 257/363 [00:07<00:03, 33.44it/s] Loading 0: 72%|███████▏ | 262/363 [00:07<00:02, 35.99it/s] Loading 0: 73%|███████▎ | 266/363 [00:07<00:02, 33.91it/s] Loading 0: 75%|███████▌ | 274/363 [00:07<00:02, 42.67it/s] Loading 0: 77%|███████▋ | 280/363 [00:07<00:01, 41.85it/s] Loading 0: 79%|███████▊ | 285/363 [00:07<00:01, 41.35it/s] Loading 0: 80%|████████ | 291/363 [00:07<00:01, 44.20it/s] Loading 0: 82%|████████▏ | 296/363 [00:08<00:01, 41.38it/s] Loading 0: 83%|████████▎ | 301/363 [00:08<00:01, 41.66it/s] Loading 0: 84%|████████▍ | 306/363 [00:15<00:24, 2.35it/s] Loading 0: 85%|████████▌ | 309/363 [00:15<00:18, 2.87it/s] Loading 0: 86%|████████▌ | 312/363 [00:15<00:14, 3.49it/s] Loading 0: 88%|████████▊ | 319/363 [00:15<00:07, 5.80it/s] Loading 0: 89%|████████▉ | 323/363 [00:15<00:05, 7.35it/s] Loading 0: 90%|█████████ | 328/363 [00:15<00:03, 10.00it/s] Loading 0: 91%|█████████▏| 332/363 [00:16<00:02, 12.23it/s] Loading 0: 93%|█████████▎| 337/363 [00:16<00:01, 15.86it/s] Loading 0: 94%|█████████▍| 341/363 [00:16<00:01, 18.34it/s] Loading 0: 95%|█████████▌| 346/363 [00:16<00:00, 22.90it/s] Loading 0: 96%|█████████▋| 350/363 [00:16<00:00, 24.90it/s] Loading 0: 98%|█████████▊| 355/363 [00:16<00:00, 29.08it/s] Loading 0: 99%|█████████▉| 359/363 [00:16<00:00, 29.39it/s]
Job cgato-nemo-12b-humanize-7413-v4-mkmlizer completed after 115.09s with status: succeeded
Stopping job with name cgato-nemo-12b-humanize-7413-v4-mkmlizer
Pipeline stage MKMLizer completed in 115.61s
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 cgato-nemo-12b-humanize-7413-v4
Waiting for inference service cgato-nemo-12b-humanize-7413-v4 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
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
Inference service cgato-nemo-12b-humanize-7413-v4 ready after 201.63699531555176s
Pipeline stage MKMLDeployer completed in 202.20s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.992314338684082s
Received healthy response to inference request in 1.6386468410491943s
Received healthy response to inference request in 1.7674369812011719s
Received healthy response to inference request in 1.2503373622894287s
Received healthy response to inference request in 1.7499616146087646s
5 requests
0 failed requests
5th percentile: 1.3279992580413817
10th percentile: 1.405661153793335
20th percentile: 1.5609849452972413
30th percentile: 1.6609097957611083
40th percentile: 1.7054357051849365
50th percentile: 1.7499616146087646
60th percentile: 1.7569517612457275
70th percentile: 1.7639419078826903
80th percentile: 1.8124124526977539
90th percentile: 1.902363395690918
95th percentile: 1.9473388671875
99th percentile: 1.9833192443847656
mean time: 1.6797394275665283
Pipeline stage StressChecker completed in 9.74s
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 2.04s
Shutdown handler de-registered
cgato-nemo-12b-humanize-_7413_v4 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 0.09s
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 cgato-nemo-12b-humanize-7413-v4-profiler
Waiting for inference service cgato-nemo-12b-humanize-7413-v4-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 3066.97s
Shutdown handler de-registered
cgato-nemo-12b-humanize-_7413_v4 status is now inactive due to auto deactivation removed underperforming models