submission_id: rica40325-iter0-2483_v1
developer_uid: rica40325
best_of: 8
celo_rating: 1251.73
display_name: rica40325-iter0-2483_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/iter0-2483
latencies: [{'batch_size': 1, 'throughput': 0.8782504696946268, 'latency_mean': 1.1385386419296264, 'latency_p50': 1.1272435188293457, 'latency_p90': 1.2514543294906617}, {'batch_size': 4, 'throughput': 1.8917564537122145, 'latency_mean': 2.1088846635818483, 'latency_p50': 2.0953123569488525, 'latency_p90': 2.3728332996368406}, {'batch_size': 5, 'throughput': 2.0286092198210857, 'latency_mean': 2.4523957002162935, 'latency_p50': 2.4506239891052246, 'latency_p90': 2.7136688470840453}, {'batch_size': 8, 'throughput': 2.2600366312237443, 'latency_mean': 3.5113612139225006, 'latency_p50': 3.500797986984253, 'latency_p90': 3.9347765922546385}, {'batch_size': 10, 'throughput': 2.3295160355490485, 'latency_mean': 4.261341555118561, 'latency_p50': 4.252498984336853, 'latency_p90': 4.837017846107483}, {'batch_size': 12, 'throughput': 2.348803644559366, 'latency_mean': 5.067901059389114, 'latency_p50': 5.088129878044128, 'latency_p90': 5.79085783958435}, {'batch_size': 15, 'throughput': 2.357799721139842, 'latency_mean': 6.276630337238312, 'latency_p50': 6.255084753036499, 'latency_p90': 7.050753402709961}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: rica40325/iter0-2483
model_name: rica40325-iter0-2483_v1
model_num_parameters: 8030261248.0
model_repo: rica40325/iter0-2483
model_size: 8B
num_battles: 58659
num_wins: 29839
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 2.3
timestamp: 2024-09-23T08:15:14+00:00
us_pacific_date: 2024-09-23
win_ratio: 0.5086857941662831
Resubmit model
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-iter0-2483-v1-mkmlizer
Waiting for job on rica40325-iter0-2483-v1-mkmlizer to finish
rica40325-iter0-2483-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
rica40325-iter0-2483-v1-mkmlizer: ║ _____ __ __ ║
rica40325-iter0-2483-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
rica40325-iter0-2483-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
rica40325-iter0-2483-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
rica40325-iter0-2483-v1-mkmlizer: ║ /___/ ║
rica40325-iter0-2483-v1-mkmlizer: ║ ║
rica40325-iter0-2483-v1-mkmlizer: ║ Version: 0.10.1 ║
rica40325-iter0-2483-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
rica40325-iter0-2483-v1-mkmlizer: ║ https://mk1.ai ║
rica40325-iter0-2483-v1-mkmlizer: ║ ║
rica40325-iter0-2483-v1-mkmlizer: ║ The license key for the current software has been verified as ║
rica40325-iter0-2483-v1-mkmlizer: ║ belonging to: ║
rica40325-iter0-2483-v1-mkmlizer: ║ ║
rica40325-iter0-2483-v1-mkmlizer: ║ Chai Research Corp. ║
rica40325-iter0-2483-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
rica40325-iter0-2483-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
rica40325-iter0-2483-v1-mkmlizer: ║ ║
rica40325-iter0-2483-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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rica40325-iter0-2483-v1-mkmlizer: Downloaded to shared memory in 62.002s
rica40325-iter0-2483-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpf7b6z3ic, device:0
rica40325-iter0-2483-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
rica40325-iter0-2483-v1-mkmlizer: quantized model in 29.089s
rica40325-iter0-2483-v1-mkmlizer: Processed model rica40325/iter0-2483 in 91.091s
rica40325-iter0-2483-v1-mkmlizer: creating bucket guanaco-mkml-models
rica40325-iter0-2483-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rica40325-iter0-2483-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rica40325-iter0-2483-v1
rica40325-iter0-2483-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rica40325-iter0-2483-v1/config.json
rica40325-iter0-2483-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rica40325-iter0-2483-v1/special_tokens_map.json
rica40325-iter0-2483-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rica40325-iter0-2483-v1/tokenizer_config.json
rica40325-iter0-2483-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rica40325-iter0-2483-v1/tokenizer.json
rica40325-iter0-2483-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/rica40325-iter0-2483-v1/flywheel_model.0.safetensors
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Job rica40325-iter0-2483-v1-mkmlizer completed after 118.47s with status: succeeded
Stopping job with name rica40325-iter0-2483-v1-mkmlizer
Pipeline stage MKMLizer completed in 119.62s
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Creating inference service rica40325-iter0-2483-v1
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Inference service rica40325-iter0-2483-v1 ready after 191.23551416397095s
Pipeline stage MKMLDeployer completed in 191.70s
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Received healthy response to inference request in 1.7008955478668213s
Received healthy response to inference request in 1.4941375255584717s
Received healthy response to inference request in 2.066218852996826s
Received healthy response to inference request in 2.245457649230957s
Received healthy response to inference request in 2.6034555435180664s
5 requests
0 failed requests
5th percentile: 1.5354891300201416
10th percentile: 1.5768407344818116
20th percentile: 1.6595439434051513
30th percentile: 1.7739602088928224
40th percentile: 1.9200895309448243
50th percentile: 2.066218852996826
60th percentile: 2.1379143714904787
70th percentile: 2.2096098899841308
80th percentile: 2.317057228088379
90th percentile: 2.4602563858032225
95th percentile: 2.5318559646606444
99th percentile: 2.589135627746582
mean time: 2.0220330238342283
Pipeline stage StressChecker completed in 12.84s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 5.42s
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Creating inference service rica40325-iter0-2483-v1-profiler
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Inference service rica40325-iter0-2483-v1-profiler ready after 190.46532487869263s
Pipeline stage MKMLProfilerDeployer completed in 190.83s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/rica40325-iter0-2483-v1-profiler-predictor-00001-deploymenlnmw9:/code/chaiverse_profiler_1727079885 --namespace tenant-chaiml-guanaco
kubectl exec -it rica40325-iter0-2483-v1-profiler-predictor-00001-deploymenlnmw9 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727079885 && 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_1727079885/summary.json'
kubectl exec -it rica40325-iter0-2483-v1-profiler-predictor-00001-deploymenlnmw9 --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727079885/summary.json'
Pipeline stage MKMLProfilerRunner completed in 782.19s
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Running pipeline stage MKMLProfilerDeleter
Checking if service rica40325-iter0-2483-v1-profiler is running
Tearing down inference service rica40325-iter0-2483-v1-profiler
Service rica40325-iter0-2483-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.86s
Shutdown handler de-registered
rica40325-iter0-2483_v1 status is now inactive due to auto deactivation removed underperforming models
rica40325-iter0-2483_v1 status is now torndown due to DeploymentManager action