submission_id: cycy233-l3-p-v1-c2_v1
developer_uid: shiroe40
best_of: 16
celo_rating: 1255.83
display_name: auto
family_friendly_score: 0.0
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{bot_name}'s Persona: {memory}\n\n", 'prompt_template': '{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}: {message}<|eot_id|>', 'user_template': '<|start_header_id|>user<|end_header_id|>\n\n{user_name}: {message}<|eot_id|>', 'response_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{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': ['<|end_header_id|>', '<|eot_id|>'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: cycy233/L3-p-v1-c2
latencies: [{'batch_size': 1, 'throughput': 0.8978860415802637, 'latency_mean': 1.1136440408229829, 'latency_p50': 1.110798954963684, 'latency_p90': 1.239614152908325}, {'batch_size': 4, 'throughput': 1.7775958588832739, 'latency_mean': 2.2427354609966277, 'latency_p50': 2.2436976432800293, 'latency_p90': 2.4811306238174438}, {'batch_size': 5, 'throughput': 1.8509397329624262, 'latency_mean': 2.6889288926124575, 'latency_p50': 2.6967735290527344, 'latency_p90': 3.0012045621871946}, {'batch_size': 8, 'throughput': 1.9831545969852538, 'latency_mean': 4.002020220756531, 'latency_p50': 3.9871100187301636, 'latency_p90': 4.533236742019653}, {'batch_size': 10, 'throughput': 1.9965572023636724, 'latency_mean': 4.95833986401558, 'latency_p50': 4.931059718132019, 'latency_p90': 5.746557188034058}, {'batch_size': 12, 'throughput': 2.010464721811011, 'latency_mean': 5.88075037240982, 'latency_p50': 5.909782886505127, 'latency_p90': 6.567594814300537}, {'batch_size': 15, 'throughput': 1.9901253852290808, 'latency_mean': 7.384539743661881, 'latency_p50': 7.523588061332703, 'latency_p90': 8.283530163764954}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: cycy233/L3-p-v1-c2
model_name: auto
model_num_parameters: 8030261248.0
model_repo: cycy233/L3-p-v1-c2
model_size: 8B
num_battles: 10992
num_wins: 5669
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.98
timestamp: 2024-09-09T03:22:43+00:00
us_pacific_date: 2024-09-08
win_ratio: 0.5157387190684134
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Shutdown handler not registered because Python interpreter is not running in the main thread
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Running pipeline stage MKMLizer
Starting job with name cycy233-l3-p-v1-c2-v1-mkmlizer
Waiting for job on cycy233-l3-p-v1-c2-v1-mkmlizer to finish
cycy233-l3-p-v1-c2-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ _____ __ __ ║
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cycy233-l3-p-v1-c2-v1-mkmlizer: ║ /___/ ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ Version: 0.10.1 ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ https://mk1.ai ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ belonging to: ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ Chai Research Corp. ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ║ ║
cycy233-l3-p-v1-c2-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-l3-p-v1-c2-v1-mkmlizer: Downloaded to shared memory in 34.642s
cycy233-l3-p-v1-c2-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpw3m7v9vw, device:0
cycy233-l3-p-v1-c2-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cycy233-l3-p-v1-c2-v1-mkmlizer: quantized model in 25.162s
cycy233-l3-p-v1-c2-v1-mkmlizer: Processed model cycy233/L3-p-v1-c2 in 59.805s
cycy233-l3-p-v1-c2-v1-mkmlizer: creating bucket guanaco-mkml-models
cycy233-l3-p-v1-c2-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-l3-p-v1-c2-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-l3-p-v1-c2-v1
cycy233-l3-p-v1-c2-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-l3-p-v1-c2-v1/config.json
cycy233-l3-p-v1-c2-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-l3-p-v1-c2-v1/special_tokens_map.json
cycy233-l3-p-v1-c2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-l3-p-v1-c2-v1/tokenizer_config.json
cycy233-l3-p-v1-c2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-l3-p-v1-c2-v1/tokenizer.json
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Job cycy233-l3-p-v1-c2-v1-mkmlizer completed after 84.03s with status: succeeded
Stopping job with name cycy233-l3-p-v1-c2-v1-mkmlizer
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Inference service cycy233-l3-p-v1-c2-v1 ready after 150.37843465805054s
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Received healthy response to inference request in 2.426102876663208s
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5th percentile: 1.676975679397583
10th percentile: 1.68910756111145
20th percentile: 1.7133713245391846
30th percentile: 1.767091655731201
40th percentile: 1.8502685546875
50th percentile: 1.9334454536437988
60th percentile: 1.9616180419921876
70th percentile: 1.9897906303405761
80th percentile: 2.088322114944458
90th percentile: 2.257212495803833
95th percentile: 2.3416576862335203
99th percentile: 2.4092138385772706
mean time: 1.950754451751709
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/cycy233-l3-p-v1-c2-v1-profiler-predictor-00001-deployment-fnlcp:/code/chaiverse_profiler_1725852604 --namespace tenant-chaiml-guanaco
kubectl exec -it cycy233-l3-p-v1-c2-v1-profiler-predictor-00001-deployment-fnlcp --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725852604 && python profiles.py profile --best_of_n 16 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 512 --output_tokens 64 --summary /code/chaiverse_profiler_1725852604/summary.json'
kubectl exec -it cycy233-l3-p-v1-c2-v1-profiler-predictor-00001-deployment-fnlcp --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725852604/summary.json'
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