submission_id: meta-llama-llama-3-1-8b-_7331_v1
developer_uid: immaculate_possum_03470
best_of: 4
celo_rating: 1189.34
display_name: red_llama
family_friendly_score: 0.6106016140865738
family_friendly_standard_error: 0.009324760326638188
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': 0.99, 'top_p': 0.2, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.5, 'frequency_penalty': 0.5, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 4, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: meta-llama/Llama-3.1-8B-Instruct
latencies: [{'batch_size': 1, 'throughput': 0.90583055987644, 'latency_mean': 1.1038896143436432, 'latency_p50': 1.0965626239776611, 'latency_p90': 1.2324304819107055}, {'batch_size': 5, 'throughput': 2.335071735230386, 'latency_mean': 2.1253840267658233, 'latency_p50': 2.108534097671509, 'latency_p90': 2.4094232320785522}, {'batch_size': 10, 'throughput': 2.851850133885135, 'latency_mean': 3.4788441896438598, 'latency_p50': 3.4426647424697876, 'latency_p90': 4.006251573562622}, {'batch_size': 15, 'throughput': 3.0192316261875347, 'latency_mean': 4.920608372688293, 'latency_p50': 4.9452409744262695, 'latency_p90': 5.661931753158569}, {'batch_size': 20, 'throughput': 2.9961295262354257, 'latency_mean': 6.550347286462784, 'latency_p50': 6.559294700622559, 'latency_p90': 7.25628068447113}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: meta-llama/Llama-3.1-8B-
model_name: red_llama
model_num_parameters: 8030261248.0
model_repo: meta-llama/Llama-3.1-8B-Instruct
model_size: 8B
num_battles: 2780
num_wins: 1185
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 2.91
timestamp: 2024-09-26T17:39:28+00:00
us_pacific_date: 2024-09-26
win_ratio: 0.4262589928057554
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Resubmit model
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name meta-llama-llama-3-1-8b-7331-v1-mkmlizer
Waiting for job on meta-llama-llama-3-1-8b-7331-v1-mkmlizer to finish
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║     _____            __           __                                ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║       /___/                                                         ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║                                                                     ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  https://mk1.ai                                                     ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║                                                                     ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  belonging to:                                                      ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║                                                                     ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  Chai Research Corp.                                                ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ║                                                                     ║
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: Downloaded to shared memory in 34.767s
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpdsrp5acy, device:0
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: quantized model in 25.973s
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: Processed model meta-llama/Llama-3.1-8B-Instruct in 60.741s
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: creating bucket guanaco-mkml-models
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/meta-llama-llama-3-1-8b-7331-v1
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/meta-llama-llama-3-1-8b-7331-v1/config.json
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/meta-llama-llama-3-1-8b-7331-v1/special_tokens_map.json
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/meta-llama-llama-3-1-8b-7331-v1/tokenizer_config.json
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/meta-llama-llama-3-1-8b-7331-v1/tokenizer.json
meta-llama-llama-3-1-8b-7331-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/meta-llama-llama-3-1-8b-7331-v1/flywheel_model.0.safetensors
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Job meta-llama-llama-3-1-8b-7331-v1-mkmlizer completed after 82.21s with status: succeeded
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Inference service meta-llama-llama-3-1-8b-7331-v1 ready after 220.5227963924408s
Pipeline stage MKMLDeployer completed in 220.86s
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Received healthy response to inference request in 2.172398090362549s
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Received healthy response to inference request in 1.1827900409698486s
Received healthy response to inference request in 1.2438576221466064s
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5th percentile: 1.1829314231872559
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mean time: 1.3969963550567628
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/meta-llama-llama-3-16f49f50ab0c43fb5935207ce8477ffce-deplo4t25t:/code/chaiverse_profiler_1727372959 --namespace tenant-chaiml-guanaco
kubectl exec -it meta-llama-llama-3-16f49f50ab0c43fb5935207ce8477ffce-deplo4t25t --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727372959 && python profiles.py profile --best_of_n 4 --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_1727372959/summary.json'
kubectl exec -it meta-llama-llama-3-16f49f50ab0c43fb5935207ce8477ffce-deplo4t25t --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727372959/summary.json'
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admin requested tearing down of mistralai-mistral-nemo_9330_v123
Cleaning model data from S3
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Shutdown handler not registered because Python interpreter is not running in the main thread
admin requested tearing down of mistralai-mistral-nemo_9330_v124
Checking if service mistralai-mistral-nemo-9330-v117 is running
Cleaning model data from model cache
Cleaning model data from S3
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Deleting key mistralai-mistral-nemo-9330-v111/special_tokens_map.json from bucket guanaco-mkml-models
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Cleaning model data from S3
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meta-llama-llama-3-1-8b-_7331_v1 status is now torndown due to DeploymentManager action
admin requested tearing down of mistralai-mistral-nemo_9330_v122
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