submission_id: epiculous-azure-dusk-v0-2_v1
developer_uid: Epiculous
best_of: 8
celo_rating: 1246.96
display_name: Azure_Dusk-v0-2-VT
family_friendly_score: 0.0
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': False}
generation_params: {'temperature': 0.95, 'top_p': 1.0, 'min_p': 0.075, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: Epiculous/Azure_Dusk-v0.2
latencies: [{'batch_size': 1, 'throughput': 0.6994590580782591, 'latency_mean': 1.4296178233623504, 'latency_p50': 1.429540753364563, 'latency_p90': 1.5880573987960815}, {'batch_size': 3, 'throughput': 1.3158091819002093, 'latency_mean': 2.2719916665554045, 'latency_p50': 2.2665045261383057, 'latency_p90': 2.5026118993759154}, {'batch_size': 5, 'throughput': 1.5703852058420236, 'latency_mean': 3.16495809674263, 'latency_p50': 3.1980167627334595, 'latency_p90': 3.5327499866485597}, {'batch_size': 6, 'throughput': 1.6251108937199585, 'latency_mean': 3.668463416099548, 'latency_p50': 3.7138158082962036, 'latency_p90': 4.130882096290589}, {'batch_size': 8, 'throughput': 1.6109153798322682, 'latency_mean': 4.942424048185348, 'latency_p50': 4.943863153457642, 'latency_p90': 5.570983576774597}, {'batch_size': 10, 'throughput': 1.563646486712016, 'latency_mean': 6.359816110134124, 'latency_p50': 6.376768350601196, 'latency_p90': 7.243695592880249}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: Epiculous/Azure_Dusk-v0.
model_name: Azure_Dusk-v0-2-VT
model_num_parameters: 12772070400.0
model_repo: Epiculous/Azure_Dusk-v0.2
model_size: 13B
num_battles: 12621
num_wins: 6485
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.64
timestamp: 2024-09-09T16:31:49+00:00
us_pacific_date: 2024-09-09
win_ratio: 0.513826162744632
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
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run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name epiculous-azure-dusk-v0-2-v1-mkmlizer
Waiting for job on epiculous-azure-dusk-v0-2-v1-mkmlizer to finish
epiculous-azure-dusk-v0-2-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ _____ __ __ ║
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epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ /___/ ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ Version: 0.10.1 ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ https://mk1.ai ║
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epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ The license key for the current software has been verified as ║
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epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ Chai Research Corp. ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║ ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
epiculous-azure-dusk-v0-2-v1-mkmlizer: quantized model in 36.542s
epiculous-azure-dusk-v0-2-v1-mkmlizer: Processed model Epiculous/Azure_Dusk-v0.2 in 82.480s
epiculous-azure-dusk-v0-2-v1-mkmlizer: creating bucket guanaco-mkml-models
epiculous-azure-dusk-v0-2-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
epiculous-azure-dusk-v0-2-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/epiculous-azure-dusk-v0-2-v1
epiculous-azure-dusk-v0-2-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/epiculous-azure-dusk-v0-2-v1/config.json
epiculous-azure-dusk-v0-2-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/epiculous-azure-dusk-v0-2-v1/special_tokens_map.json
epiculous-azure-dusk-v0-2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/epiculous-azure-dusk-v0-2-v1/tokenizer_config.json
epiculous-azure-dusk-v0-2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/epiculous-azure-dusk-v0-2-v1/tokenizer.json
epiculous-azure-dusk-v0-2-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/epiculous-azure-dusk-v0-2-v1/flywheel_model.0.safetensors
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Job epiculous-azure-dusk-v0-2-v1-mkmlizer completed after 105.18s with status: succeeded
Stopping job with name epiculous-azure-dusk-v0-2-v1-mkmlizer
Pipeline stage MKMLizer completed in 107.76s
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Inference service epiculous-azure-dusk-v0-2-v1 ready after 150.62637901306152s
Pipeline stage MKMLDeployer completed in 151.04s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.538109064102173s
Received healthy response to inference request in 2.048007011413574s
Received healthy response to inference request in 1.7887613773345947s
Received healthy response to inference request in 2.441253423690796s
Received healthy response to inference request in 2.749952793121338s
5 requests
0 failed requests
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mean time: 2.313216733932495
Pipeline stage StressChecker completed in 12.19s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 8.44s
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Inference service epiculous-azure-dusk-v0-2-v1-profiler ready after 150.33491110801697s
Pipeline stage MKMLProfilerDeployer completed in 150.71s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/epiculous-azure-dusk15987d7b26bee69a27de9c86cf03fce6-deplo57n9n:/code/chaiverse_profiler_1725899979 --namespace tenant-chaiml-guanaco
kubectl exec -it epiculous-azure-dusk15987d7b26bee69a27de9c86cf03fce6-deplo57n9n --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725899979 && python profiles.py profile --best_of_n 8 --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_1725899979/summary.json'
kubectl exec -it epiculous-azure-dusk15987d7b26bee69a27de9c86cf03fce6-deplo57n9n --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725899979/summary.json'
Pipeline stage MKMLProfilerRunner completed in 946.81s
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Running pipeline stage MKMLProfilerDeleter
Checking if service epiculous-azure-dusk-v0-2-v1-profiler is running
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Pipeline stage MKMLProfilerDeleter completed in 1.82s
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epiculous-azure-dusk-v0-2_v1 status is now inactive due to auto deactivation removed underperforming models
epiculous-azure-dusk-v0-2_v1 status is now torndown due to DeploymentManager action