submission_id: cycy233-l3-p-v4-c1_v1
developer_uid: shiroe40
best_of: 16
celo_rating: 1250.05
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-v4-c1
latencies: [{'batch_size': 1, 'throughput': 0.9041786756678538, 'latency_mean': 1.105915765762329, 'latency_p50': 1.1005918979644775, 'latency_p90': 1.2423787117004395}, {'batch_size': 4, 'throughput': 1.8089813169171738, 'latency_mean': 2.200504150390625, 'latency_p50': 2.1787039041519165, 'latency_p90': 2.524139165878296}, {'batch_size': 5, 'throughput': 1.8742952826490942, 'latency_mean': 2.6530987417697904, 'latency_p50': 2.659836173057556, 'latency_p90': 2.9565185546875}, {'batch_size': 8, 'throughput': 1.9943646212768293, 'latency_mean': 3.984754989147186, 'latency_p50': 3.992251992225647, 'latency_p90': 4.483180594444275}, {'batch_size': 10, 'throughput': 2.01448827925604, 'latency_mean': 4.912209231853485, 'latency_p50': 4.876551985740662, 'latency_p90': 5.57101674079895}, {'batch_size': 12, 'throughput': 2.0235987682261882, 'latency_mean': 5.848695582151413, 'latency_p50': 5.8558759689331055, 'latency_p90': 6.676494932174682}, {'batch_size': 15, 'throughput': 2.0161133801517934, 'latency_mean': 7.295335454940796, 'latency_p50': 7.400796890258789, 'latency_p90': 8.184788537025451}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: cycy233/L3-p-v4-c1
model_name: auto
model_num_parameters: 8030261248.0
model_repo: cycy233/L3-p-v4-c1
model_size: 8B
num_battles: 10383
num_wins: 5267
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.99
timestamp: 2024-09-13T02:19:50+00:00
us_pacific_date: 2024-09-12
win_ratio: 0.5072715014928249
Resubmit model
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Running pipeline stage MKMLizer
Starting job with name cycy233-l3-p-v4-c1-v1-mkmlizer
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cycy233-l3-p-v4-c1-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ _____ __ __ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ /___/ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ Version: 0.10.1 ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ https://mk1.ai ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ belonging to: ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ Chai Research Corp. ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-l3-p-v4-c1-v1-mkmlizer: Downloaded to shared memory in 35.423s
cycy233-l3-p-v4-c1-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpcjbw2grc, device:0
cycy233-l3-p-v4-c1-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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cycy233-l3-p-v4-c1-v1-mkmlizer: quantized model in 25.847s
cycy233-l3-p-v4-c1-v1-mkmlizer: Processed model cycy233/L3-p-v4-c1 in 61.271s
cycy233-l3-p-v4-c1-v1-mkmlizer: creating bucket guanaco-mkml-models
cycy233-l3-p-v4-c1-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-l3-p-v4-c1-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v1
cycy233-l3-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v1/config.json
cycy233-l3-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v1/special_tokens_map.json
cycy233-l3-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v1/tokenizer_config.json
cycy233-l3-p-v4-c1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v1/tokenizer.json
Job cycy233-l3-p-v4-c1-v1-mkmlizer completed after 86.0s with status: succeeded
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Creating inference service cycy233-l3-p-v4-c1-v1
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Inference service cycy233-l3-p-v4-c1-v1 ready after 161.05349040031433s
Pipeline stage MKMLDeployer completed in 161.42s
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Received healthy response to inference request in 2.134166717529297s
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Received healthy response to inference request in 1.7102432250976562s
Received healthy response to inference request in 2.1853885650634766s
Received healthy response to inference request in 1.7119512557983398s
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5th percentile: 1.6725589752197265
10th percentile: 1.681980037689209
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mean time: 1.8809775352478026
Pipeline stage StressChecker completed in 10.25s
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Inference service cycy233-l3-p-v4-c1-v1-profiler ready after 170.40005493164062s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/cycy233-l3-p-v4-c1-v1-profiler-predictor-00001-deployment-6ts5v:/code/chaiverse_profiler_1726194474 --namespace tenant-chaiml-guanaco
kubectl exec -it cycy233-l3-p-v4-c1-v1-profiler-predictor-00001-deployment-6ts5v --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726194474 && 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_1726194474/summary.json'
kubectl exec -it cycy233-l3-p-v4-c1-v1-profiler-predictor-00001-deployment-6ts5v --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726194474/summary.json'
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