submission_id: jic062-nemo-v1-2_v2
developer_uid: chace9580
alignment_samples: 12731
alignment_score: 0.35694978275517764
best_of: 8
celo_rating: 1262.17
display_name: jic062-nemo-v1-2_v2
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{bot_name}'s Persona: {memory}\n\n", 'prompt_template': '{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}: {message}<|eot_id|>', 'user_template': '<|start_header_id|>user<|end_header_id|>\n\n{user_name}: {message}<|eot_id|>', 'response_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 0.75, 'top_p': 1.0, 'min_p': 0.1, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '<|im_end|>', '<|end_of_text|>', '|eot_id|'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64}
is_internal_developer: False
language_model: jic062/Nemo-v1.2
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: jic062/Nemo-v1.2
model_name: jic062-nemo-v1-2_v2
model_num_parameters: 12772070400.0
model_repo: jic062/Nemo-v1.2
model_size: 13B
num_battles: 12731
num_wins: 6763
propriety_score: 0.7126654064272212
propriety_total_count: 1058.0
ranking_group: single
status: inactive
submission_type: basic
timestamp: 2024-09-04T04:24:14+00:00
us_pacific_date: 2024-09-03
win_ratio: 0.5312229989788705
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Running pipeline stage MKMLizer
Starting job with name jic062-nemo-v1-2-v2-mkmlizer
Waiting for job on jic062-nemo-v1-2-v2-mkmlizer to finish
jic062-nemo-v1-2-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
jic062-nemo-v1-2-v2-mkmlizer: ║ _____ __ __ ║
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jic062-nemo-v1-2-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
jic062-nemo-v1-2-v2-mkmlizer: ║ /___/ ║
jic062-nemo-v1-2-v2-mkmlizer: ║ ║
jic062-nemo-v1-2-v2-mkmlizer: ║ Version: 0.10.1 ║
jic062-nemo-v1-2-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
jic062-nemo-v1-2-v2-mkmlizer: ║ https://mk1.ai ║
jic062-nemo-v1-2-v2-mkmlizer: ║ ║
jic062-nemo-v1-2-v2-mkmlizer: ║ The license key for the current software has been verified as ║
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jic062-nemo-v1-2-v2-mkmlizer: ║ ║
jic062-nemo-v1-2-v2-mkmlizer: ║ Chai Research Corp. ║
jic062-nemo-v1-2-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
jic062-nemo-v1-2-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
jic062-nemo-v1-2-v2-mkmlizer: ║ ║
jic062-nemo-v1-2-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
jic062-nemo-v1-2-v2-mkmlizer: Downloaded to shared memory in 53.488s
jic062-nemo-v1-2-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpyxovwe2u, device:0
jic062-nemo-v1-2-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
jic062-nemo-v1-2-v2-mkmlizer: quantized model in 35.916s
jic062-nemo-v1-2-v2-mkmlizer: Processed model jic062/Nemo-v1.2 in 89.404s
jic062-nemo-v1-2-v2-mkmlizer: creating bucket guanaco-mkml-models
jic062-nemo-v1-2-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jic062-nemo-v1-2-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jic062-nemo-v1-2-v2
jic062-nemo-v1-2-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v2/config.json
jic062-nemo-v1-2-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v2/special_tokens_map.json
jic062-nemo-v1-2-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v2/tokenizer_config.json
jic062-nemo-v1-2-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jic062-nemo-v1-2-v2/tokenizer.json
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Job jic062-nemo-v1-2-v2-mkmlizer completed after 114.91s with status: succeeded
Stopping job with name jic062-nemo-v1-2-v2-mkmlizer
Pipeline stage MKMLizer completed in 116.50s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.09s
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Running pipeline stage MKMLDeployer
Creating inference service jic062-nemo-v1-2-v2
Waiting for inference service jic062-nemo-v1-2-v2 to be ready
Connection pool is full, discarding connection: %s. Connection pool size: %s
Inference service jic062-nemo-v1-2-v2 ready after 140.6555209159851s
Pipeline stage MKMLDeployer completed in 141.01s
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Running pipeline stage StressChecker
Received healthy response to inference request in 3.1753616333007812s
Received healthy response to inference request in 2.0678799152374268s
Received healthy response to inference request in 2.2230207920074463s
Received healthy response to inference request in 1.8592779636383057s
Received healthy response to inference request in 2.4255595207214355s
5 requests
0 failed requests
5th percentile: 1.9009983539581299
10th percentile: 1.942718744277954
20th percentile: 2.0261595249176025
30th percentile: 2.0989080905914306
40th percentile: 2.1609644412994387
50th percentile: 2.2230207920074463
60th percentile: 2.304036283493042
70th percentile: 2.3850517749786375
80th percentile: 2.575519943237305
90th percentile: 2.875440788269043
95th percentile: 3.0254012107849118
99th percentile: 3.1453695487976074
mean time: 2.350219964981079
Pipeline stage StressChecker completed in 12.54s
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Running pipeline stage TriggerMKMLProfilingPipeline
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Pipeline stage TriggerMKMLProfilingPipeline completed in 8.77s
jic062-nemo-v1-2_v2 status is now deployed due to DeploymentManager action
registered shutdown handler
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.12s
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Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service jic062-nemo-v1-2-v2-profiler
Waiting for inference service jic062-nemo-v1-2-v2-profiler to be ready
Inference service jic062-nemo-v1-2-v2-profiler ready after 150.38212895393372s
Pipeline stage MKMLProfilerDeployer completed in 150.75s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-nemo-v1-2-v2-profiler-predictor-00001-deployment-79sj9jr:/code/chaiverse_profiler_1725424333 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-nemo-v1-2-v2-profiler-predictor-00001-deployment-79sj9jr --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725424333 && 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_1725424333/summary.json'
Received SIGINT, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service jic062-nemo-v1-2-v2-profiler is running
Tearing down inference service jic062-nemo-v1-2-v2-profiler
Service jic062-nemo-v1-2-v2-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.50s
de-registered shutdown handler
jic062-nemo-v1-2_v2 status is now inactive due to auto deactivation removed underperforming models

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