epiculous-azure-dusk-v0-2

submission_id: epiculous-azure-dusk-v0-2_v1

developer_uid: Epiculous

alignment_samples: 12621

alignment_score: -0.8419456599799823

best_of: 8

celo_rating: 1246.8

display_name: Azure_Dusk-v0-2-VT

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

propriety_score: 0.7377938517179023

propriety_total_count: 1106.0

ranking_group: single

status: inactive

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

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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 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: ║     _____            __           __                                ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
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                                                     ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║                                                                     ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║  belonging to:                                                      ║
epiculous-azure-dusk-v0-2-v1-mkmlizer: ║                                                                     ║
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
epiculous-azure-dusk-v0-2-v1-mkmlizer: 
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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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Creating inference service epiculous-azure-dusk-v0-2-v1
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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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Received healthy response to inference request in 2.538109064102173s
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mean time: 2.313216733932495
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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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Running pipeline stage MKMLProfilerRunner
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
Tearing down inference service epiculous-azure-dusk-v0-2-v1-profiler
Service epiculous-azure-dusk-v0-2-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.82s
Shutdown handler de-registered
epiculous-azure-dusk-v0-2_v1 status is now inactive due to auto deactivation removed underperforming models