riverise-mistral-0920

submission_id: riverise-mistral-0920_v3

developer_uid: Riverise

best_of: 8

celo_rating: 1252.92

display_name: riverise-mistral-0920_v3

family_friendly_score: 0.0

formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}

generation_params: {'temperature': 1.15, 'top_p': 0.95, 'min_p': 0.05, 'top_k': 30, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}

gpu_counts: {'NVIDIA RTX A5000': 1}

is_internal_developer: False

language_model: Riverise/mistral_0920

latencies: [{'batch_size': 1, 'throughput': 0.6166913448463864, 'latency_mean': 1.6214919376373291, 'latency_p50': 1.6227867603302002, 'latency_p90': 1.773893117904663}, {'batch_size': 3, 'throughput': 1.0918109990618825, 'latency_mean': 2.7433987522125243, 'latency_p50': 2.737950921058655, 'latency_p90': 3.0424190521240235}, {'batch_size': 5, 'throughput': 1.232504072533467, 'latency_mean': 4.041522045135498, 'latency_p50': 4.045285701751709, 'latency_p90': 4.463338112831115}, {'batch_size': 6, 'throughput': 1.26916105742702, 'latency_mean': 4.709285593032837, 'latency_p50': 4.7595168352127075, 'latency_p90': 5.334226512908936}, {'batch_size': 8, 'throughput': 1.2494969679492343, 'latency_mean': 6.3805814504623415, 'latency_p50': 6.3929126262664795, 'latency_p90': 7.155306124687195}, {'batch_size': 10, 'throughput': 1.211690918900314, 'latency_mean': 8.202978187799454, 'latency_p50': 8.284517407417297, 'latency_p90': 9.320258641242981}]

max_input_tokens: 1024

max_output_tokens: 64

model_architecture: MistralForCausalLM

model_group: Riverise/mistral_0920

model_name: riverise-mistral-0920_v3

model_num_parameters: 12772070400.0

model_repo: Riverise/mistral_0920

model_size: 13B

num_battles: 369574

num_wins: 187348

ranking_group: single

status: torndown

submission_type: basic

throughput_3p7s: 1.21

timestamp: 2024-09-21T09:37:41+00:00

us_pacific_date: 2024-09-21

win_ratio: 0.5069296000259759

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Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
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Running pipeline stage MKMLizer
Starting job with name riverise-mistral-0920-v3-mkmlizer
Waiting for job on riverise-mistral-0920-v3-mkmlizer to finish
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riverise-mistral-0920-v3-mkmlizer: ║     _____            __           __                                ║
riverise-mistral-0920-v3-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
riverise-mistral-0920-v3-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
riverise-mistral-0920-v3-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
riverise-mistral-0920-v3-mkmlizer: ║       /___/                                                         ║
riverise-mistral-0920-v3-mkmlizer: ║                                                                     ║
riverise-mistral-0920-v3-mkmlizer: ║  Version: 0.10.1                                                    ║
riverise-mistral-0920-v3-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
riverise-mistral-0920-v3-mkmlizer: ║  https://mk1.ai                                                     ║
riverise-mistral-0920-v3-mkmlizer: ║                                                                     ║
riverise-mistral-0920-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
riverise-mistral-0920-v3-mkmlizer: ║  belonging to:                                                      ║
riverise-mistral-0920-v3-mkmlizer: ║                                                                     ║
riverise-mistral-0920-v3-mkmlizer: ║  Chai Research Corp.                                                ║
riverise-mistral-0920-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
riverise-mistral-0920-v3-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
riverise-mistral-0920-v3-mkmlizer: ║                                                                     ║
riverise-mistral-0920-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Failed to get response for submission mistralai-mistral-small_5341_v11: ('http://mistralai-mistral-small-5341-v11-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'request timeout')
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riverise-mistral-0920-v3-mkmlizer: Downloaded to shared memory in 48.992s
riverise-mistral-0920-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpg_mt7msy, device:0
riverise-mistral-0920-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
riverise-mistral-0920-v3-mkmlizer: quantized model in 37.201s
riverise-mistral-0920-v3-mkmlizer: Processed model Riverise/mistral_0920 in 86.193s
riverise-mistral-0920-v3-mkmlizer: creating bucket guanaco-mkml-models
riverise-mistral-0920-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
riverise-mistral-0920-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/riverise-mistral-0920-v3
riverise-mistral-0920-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/riverise-mistral-0920-v3/special_tokens_map.json
riverise-mistral-0920-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/riverise-mistral-0920-v3/config.json
riverise-mistral-0920-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/riverise-mistral-0920-v3/tokenizer_config.json
riverise-mistral-0920-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/riverise-mistral-0920-v3/tokenizer.json
Failed to get response for submission mistralai-mistral-small_5341_v11: ('http://mistralai-mistral-small-5341-v11-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'request timeout')
riverise-mistral-0920-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/riverise-mistral-0920-v3/flywheel_model.0.safetensors
riverise-mistral-0920-v3-mkmlizer: 
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Job riverise-mistral-0920-v3-mkmlizer completed after 114.96s with status: succeeded
Stopping job with name riverise-mistral-0920-v3-mkmlizer
Pipeline stage MKMLizer completed in 115.76s
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Pipeline stage MKMLTemplater completed in 0.09s
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Creating inference service riverise-mistral-0920-v3
Waiting for inference service riverise-mistral-0920-v3 to be ready
Failed to get response for submission mistralai-mistral-small_5341_v11: ('http://mistralai-mistral-small-5341-v11-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'request timeout')
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Failed to get response for submission function_sabet_2024-09-10: ('http://zonemercy-virgo-edit-v1-1e5-v13-predictor.tenant-chaiml-guanaco.k2.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:41580->127.0.0.1:8080: read: connection reset by peer\n')
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Inference service riverise-mistral-0920-v3 ready after 200.59945440292358s
Pipeline stage MKMLDeployer completed in 202.94s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.594782590866089s
Received healthy response to inference request in 6.38529109954834s
Received healthy response to inference request in 2.4773550033569336s
Received healthy response to inference request in 1.834538459777832s
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Received healthy response to inference request in 3.3108770847320557s
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90th percentile: 5.155525493621827
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99th percentile: 6.262314538955688
mean time: 3.32056884765625
Pipeline stage StressChecker completed in 27.35s
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Creating inference service riverise-mistral-0920-v3-profiler
Waiting for inference service riverise-mistral-0920-v3-profiler to be ready
Inference service riverise-mistral-0920-v3-profiler ready after 190.43591856956482s
Pipeline stage MKMLProfilerDeployer completed in 193.21s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/riverise-mistral-0920-v3-profiler-predictor-00001-deploymejhp86:/code/chaiverse_profiler_1726912057 --namespace tenant-chaiml-guanaco
kubectl exec -it riverise-mistral-0920-v3-profiler-predictor-00001-deploymejhp86 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726912057 && 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 1024 --output_tokens 64 --summary /code/chaiverse_profiler_1726912057/summary.json'
kubectl exec -it riverise-mistral-0920-v3-profiler-predictor-00001-deploymejhp86 --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726912057/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1171.10s
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Running pipeline stage MKMLProfilerDeleter
Checking if service riverise-mistral-0920-v3-profiler is running
Tearing down inference service riverise-mistral-0920-v3-profiler
Service riverise-mistral-0920-v3-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 4.57s
Shutdown handler de-registered
riverise-mistral-0920_v3 status is now inactive due to auto deactivation removed underperforming models
riverise-mistral-0920_v3 status is now torndown due to DeploymentManager action