submission_id: rica40325-iter0-00_v1
developer_uid: rica40325
best_of: 8
celo_rating: 1255.02
display_name: rica40325-iter0-00_v1
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': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, '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: rica40325/iter0-00
latencies: [{'batch_size': 1, 'throughput': 0.8621361083621609, 'latency_mean': 1.159847538471222, 'latency_p50': 1.1688663959503174, 'latency_p90': 1.282182502746582}, {'batch_size': 4, 'throughput': 1.8533933744190787, 'latency_mean': 2.1483579194545745, 'latency_p50': 2.1562057733535767, 'latency_p90': 2.403863978385925}, {'batch_size': 5, 'throughput': 1.9957772955717923, 'latency_mean': 2.492143086194992, 'latency_p50': 2.467082977294922, 'latency_p90': 2.8007991313934326}, {'batch_size': 8, 'throughput': 2.2174669503673154, 'latency_mean': 3.5762291598320006, 'latency_p50': 3.5850510597229004, 'latency_p90': 3.9467114210128784}, {'batch_size': 10, 'throughput': 2.261321401035185, 'latency_mean': 4.383173420429229, 'latency_p50': 4.407534599304199, 'latency_p90': 4.951479935646057}, {'batch_size': 12, 'throughput': 2.3147904754854247, 'latency_mean': 5.143839471340179, 'latency_p50': 5.163961410522461, 'latency_p90': 5.914806604385376}, {'batch_size': 15, 'throughput': 2.3279765557671044, 'latency_mean': 6.362163634300232, 'latency_p50': 6.356178879737854, 'latency_p90': 7.162649154663086}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: rica40325/iter0-00
model_name: rica40325-iter0-00_v1
model_num_parameters: 8030261248.0
model_repo: rica40325/iter0-00
model_size: 8B
num_battles: 70629
num_wins: 36239
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 2.25
timestamp: 2024-09-23T05:23:31+00:00
us_pacific_date: 2024-09-22
win_ratio: 0.5130895241331465
Download Preference Data
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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 rica40325-iter0-00-v1-mkmlizer
Waiting for job on rica40325-iter0-00-v1-mkmlizer to finish
rica40325-iter0-00-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
rica40325-iter0-00-v1-mkmlizer: ║ _____ __ __ ║
rica40325-iter0-00-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
rica40325-iter0-00-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
rica40325-iter0-00-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
rica40325-iter0-00-v1-mkmlizer: ║ /___/ ║
rica40325-iter0-00-v1-mkmlizer: ║ ║
rica40325-iter0-00-v1-mkmlizer: ║ Version: 0.10.1 ║
rica40325-iter0-00-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
rica40325-iter0-00-v1-mkmlizer: ║ https://mk1.ai ║
rica40325-iter0-00-v1-mkmlizer: ║ ║
rica40325-iter0-00-v1-mkmlizer: ║ The license key for the current software has been verified as ║
rica40325-iter0-00-v1-mkmlizer: ║ belonging to: ║
rica40325-iter0-00-v1-mkmlizer: ║ ║
rica40325-iter0-00-v1-mkmlizer: ║ Chai Research Corp. ║
rica40325-iter0-00-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
rica40325-iter0-00-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
rica40325-iter0-00-v1-mkmlizer: ║ ║
rica40325-iter0-00-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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rica40325-iter0-00-v1-mkmlizer: Downloaded to shared memory in 60.890s
rica40325-iter0-00-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpjsobjk8e, device:0
rica40325-iter0-00-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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rica40325-iter0-00-v1-mkmlizer: quantized model in 28.346s
rica40325-iter0-00-v1-mkmlizer: Processed model rica40325/iter0-00 in 89.237s
rica40325-iter0-00-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rica40325-iter0-00-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rica40325-iter0-00-v1
rica40325-iter0-00-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rica40325-iter0-00-v1/config.json
rica40325-iter0-00-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rica40325-iter0-00-v1/special_tokens_map.json
rica40325-iter0-00-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rica40325-iter0-00-v1/tokenizer_config.json
rica40325-iter0-00-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rica40325-iter0-00-v1/tokenizer.json
rica40325-iter0-00-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/rica40325-iter0-00-v1/flywheel_model.0.safetensors
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Job rica40325-iter0-00-v1-mkmlizer completed after 113.86s with status: succeeded
Stopping job with name rica40325-iter0-00-v1-mkmlizer
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Inference service rica40325-iter0-00-v1 ready after 190.7487678527832s
Pipeline stage MKMLDeployer completed in 191.11s
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Received healthy response to inference request in 2.3930280208587646s
Received healthy response to inference request in 1.8188869953155518s
Received healthy response to inference request in 2.085616111755371s
Received healthy response to inference request in 1.3531343936920166s
Received healthy response to inference request in 1.84228515625s
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5th percentile: 1.4462849140167235
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90th percentile: 2.2700632572174073
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mean time: 1.8985901355743409
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Inference service rica40325-iter0-00-v1-profiler ready after 180.46917033195496s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/rica40325-iter0-00-v1-profiler-predictor-00001-deployment-gdm5x:/code/chaiverse_profiler_1727069562 --namespace tenant-chaiml-guanaco
kubectl exec -it rica40325-iter0-00-v1-profiler-predictor-00001-deployment-gdm5x --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727069562 && 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_1727069562/summary.json'
kubectl exec -it rica40325-iter0-00-v1-profiler-predictor-00001-deployment-gdm5x --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727069562/summary.json'
Pipeline stage MKMLProfilerRunner completed in 795.38s
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Checking if service rica40325-iter0-00-v1-profiler is running
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rica40325-iter0-00_v1 status is now inactive due to auto deactivation removed underperforming models
rica40325-iter0-00_v1 status is now torndown due to DeploymentManager action