submission_id: epiculous-azure-dusk-bas_2210_v1
developer_uid: Epiculous
alignment_samples: 12607
alignment_score: -0.48518306375304976
best_of: 8
celo_rating: 1245.67
display_name: Azure_Dusk-v0-2-NORP_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-Base-Instruct-v0.2
latencies: [{'batch_size': 1, 'throughput': 0.7023891351029451, 'latency_mean': 1.423653531074524, 'latency_p50': 1.4138360023498535, 'latency_p90': 1.6003567934036256}, {'batch_size': 3, 'throughput': 1.3508482691330608, 'latency_mean': 2.2108935010433197, 'latency_p50': 2.198080539703369, 'latency_p90': 2.446429681777954}, {'batch_size': 5, 'throughput': 1.611367776016812, 'latency_mean': 3.081811366081238, 'latency_p50': 3.091226577758789, 'latency_p90': 3.5114348888397218}, {'batch_size': 6, 'throughput': 1.6433166879847458, 'latency_mean': 3.6401929163932802, 'latency_p50': 3.6475054025650024, 'latency_p90': 4.104503345489502}, {'batch_size': 8, 'throughput': 1.5961490827090135, 'latency_mean': 4.997523243427277, 'latency_p50': 4.984360098838806, 'latency_p90': 5.648513698577881}, {'batch_size': 10, 'throughput': 1.5418442305002469, 'latency_mean': 6.444088622331619, 'latency_p50': 6.483338356018066, 'latency_p90': 7.452718663215637}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: Epiculous/Azure_Dusk-Bas
model_name: Azure_Dusk-v0-2-NORP_VT
model_num_parameters: 12772070400.0
model_repo: Epiculous/Azure_Dusk-Base-Instruct-v0.2
model_size: 13B
num_battles: 12604
num_wins: 6336
propriety_score: 0.7174887892376681
propriety_total_count: 1115.0
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.65
timestamp: 2024-09-11T00:45:13+00:00
us_pacific_date: 2024-09-10
win_ratio: 0.5026975563313234
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name epiculous-azure-dusk-bas-2210-v1-mkmlizer
Waiting for job on epiculous-azure-dusk-bas-2210-v1-mkmlizer to finish
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ _____ __ __ ║
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epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ /___/ ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ Version: 0.10.1 ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ https://mk1.ai ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ The license key for the current software has been verified as ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ belonging to: ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ Chai Research Corp. ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ║ ║
epiculous-azure-dusk-bas-2210-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
epiculous-azure-dusk-bas-2210-v1-mkmlizer: Downloaded to shared memory in 45.637s
epiculous-azure-dusk-bas-2210-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp89jrg3pn, device:0
epiculous-azure-dusk-bas-2210-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
epiculous-azure-dusk-bas-2210-v1-mkmlizer: quantized model in 35.403s
epiculous-azure-dusk-bas-2210-v1-mkmlizer: Processed model Epiculous/Azure_Dusk-Base-Instruct-v0.2 in 81.040s
epiculous-azure-dusk-bas-2210-v1-mkmlizer: creating bucket guanaco-mkml-models
epiculous-azure-dusk-bas-2210-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
epiculous-azure-dusk-bas-2210-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/epiculous-azure-dusk-bas-2210-v1
epiculous-azure-dusk-bas-2210-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/epiculous-azure-dusk-bas-2210-v1/config.json
epiculous-azure-dusk-bas-2210-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/epiculous-azure-dusk-bas-2210-v1/special_tokens_map.json
epiculous-azure-dusk-bas-2210-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/epiculous-azure-dusk-bas-2210-v1/tokenizer_config.json
epiculous-azure-dusk-bas-2210-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/epiculous-azure-dusk-bas-2210-v1/tokenizer.json
Connection pool is full, discarding connection: %s. Connection pool size: %s
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epiculous-azure-dusk-bas-2210-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/epiculous-azure-dusk-bas-2210-v1/flywheel_model.0.safetensors
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Job epiculous-azure-dusk-bas-2210-v1-mkmlizer completed after 106.08s with status: succeeded
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Creating inference service epiculous-azure-dusk-bas-2210-v1
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Inference service epiculous-azure-dusk-bas-2210-v1 ready after 150.8796842098236s
Pipeline stage MKMLDeployer completed in 151.26s
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Received healthy response to inference request in 2.2794485092163086s
Received healthy response to inference request in 2.003941059112549s
Received healthy response to inference request in 1.749812364578247s
Received healthy response to inference request in 2.016951560974121s
Received healthy response to inference request in 2.042680263519287s
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90th percentile: 2.1847412109375
95th percentile: 2.2320948600769044
99th percentile: 2.269977779388428
mean time: 2.0185667514801025
Pipeline stage StressChecker completed in 11.07s
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Inference service epiculous-azure-dusk-bas-2210-v1-profiler ready after 150.3674829006195s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/epiculous-azure-dusk84152fd1bbe77e6d523b72059ae6221d-deplolvmzj:/code/chaiverse_profiler_1726015982 --namespace tenant-chaiml-guanaco
kubectl exec -it epiculous-azure-dusk84152fd1bbe77e6d523b72059ae6221d-deplolvmzj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726015982 && 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_1726015982/summary.json'
kubectl exec -it epiculous-azure-dusk84152fd1bbe77e6d523b72059ae6221d-deplolvmzj --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726015982/summary.json'
Pipeline stage MKMLProfilerRunner completed in 938.50s
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Checking if service epiculous-azure-dusk-bas-2210-v1-profiler is running
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Service epiculous-azure-dusk-bas-2210-v1-profiler has been torndown
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Shutdown handler de-registered
epiculous-azure-dusk-bas_2210_v1 status is now inactive due to auto deactivation removed underperforming models