developer_uid: immaculate_possum_03470
submission_id: meta-llama-llama-3-1-8b-_7331_v1
model_name: red_llama
model_group: meta-llama/Llama-3.1-8B-
status: torndown
timestamp: 2024-09-26T17:39:28+00:00
num_battles: 2780
num_wins: 1185
celo_rating: 1189.34
family_friendly_score: 0.6106016140865738
family_friendly_standard_error: 0.009324760326638188
submission_type: basic
model_repo: meta-llama/Llama-3.1-8B-Instruct
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 4
max_input_tokens: 1024
max_output_tokens: 64
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}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: red_llama
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: meta-llama/Llama-3.1-8B-Instruct
model_size: 8B
ranking_group: single
throughput_3p7s: 2.91
us_pacific_date: 2024-09-26
win_ratio: 0.4262589928057554
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}
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}
Resubmit model
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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
Stopping job with name meta-llama-llama-3-1-8b-7331-v1-mkmlizer
Pipeline stage MKMLizer completed in 83.00s
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Creating inference service meta-llama-llama-3-1-8b-7331-v1
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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
Received healthy response to inference request in 1.2024390697479248s
Received healthy response to inference request in 1.1834969520568848s
Received healthy response to inference request in 1.1827900409698486s
Received healthy response to inference request in 1.2438576221466064s
5 requests
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5th percentile: 1.1829314231872559
10th percentile: 1.183072805404663
20th percentile: 1.1833555698394775
30th percentile: 1.1872853755950927
40th percentile: 1.1948622226715089
50th percentile: 1.2024390697479248
60th percentile: 1.2190064907073974
70th percentile: 1.23557391166687
80th percentile: 1.4295657157897952
90th percentile: 1.800981903076172
95th percentile: 1.98668999671936
99th percentile: 2.135256471633911
mean time: 1.3969963550567628
Pipeline stage StressChecker completed in 7.62s
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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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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
Shutdown handler not registered because Python interpreter is not running in the main thread
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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