submission_id: mistralai-mistral-nemo_9330_v112
developer_uid: immaculate_possum_03470
best_of: 8
celo_rating: 1229.88
display_name: nemo_base_1
family_friendly_score: 0.5885236447520185
family_friendly_standard_error: 0.007212565248304266
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': 0.9, 'min_p': 0.05, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: mistralai/Mistral-Nemo-Instruct-2407
latencies: [{'batch_size': 1, 'throughput': 0.6095366902346381, 'latency_mean': 1.640497829914093, 'latency_p50': 1.6368987560272217, 'latency_p90': 1.8148065328598022}, {'batch_size': 3, 'throughput': 1.0723027244301666, 'latency_mean': 2.7898495042324067, 'latency_p50': 2.7940750122070312, 'latency_p90': 3.141824913024902}, {'batch_size': 5, 'throughput': 1.2110464790536202, 'latency_mean': 4.103137856721878, 'latency_p50': 4.100713491439819, 'latency_p90': 4.690936470031739}, {'batch_size': 6, 'throughput': 1.2462005319075202, 'latency_mean': 4.798190004825592, 'latency_p50': 4.777033090591431, 'latency_p90': 5.364623045921325}, {'batch_size': 8, 'throughput': 1.2247195752396365, 'latency_mean': 6.486435064077377, 'latency_p50': 6.562326431274414, 'latency_p90': 7.235179662704468}, {'batch_size': 10, 'throughput': 1.1925532404192902, 'latency_mean': 8.343532319068908, 'latency_p50': 8.439287185668945, 'latency_p90': 9.561052703857422}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: mistralai/Mistral-Nemo-I
model_name: nemo_base_1
model_num_parameters: 12772070400.0
model_repo: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
num_battles: 4760
num_wins: 2261
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.19
timestamp: 2024-09-26T18:54:53+00:00
us_pacific_date: 2024-09-26
win_ratio: 0.475
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run pipeline %s
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Running pipeline stage MKMLizer
Starting job with name mistralai-mistral-nemo-9330-v112-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v112-mkmlizer to finish
mistralai-mistral-nemo-9330-v112-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ _____ __ __ ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ /___/ ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ Version: 0.11.12 ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ https://mk1.ai ║
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mistralai-mistral-nemo-9330-v112-mkmlizer: ║ The license key for the current software has been verified as ║
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mistralai-mistral-nemo-9330-v112-mkmlizer: ║ Chai Research Corp. ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ║ ║
mistralai-mistral-nemo-9330-v112-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v112-mkmlizer: Downloaded to shared memory in 50.096s
mistralai-mistral-nemo-9330-v112-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpsj4kwm21, device:0
mistralai-mistral-nemo-9330-v112-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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mistralai-mistral-nemo-9330-v112-mkmlizer: quantized model in 36.151s
mistralai-mistral-nemo-9330-v112-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 86.247s
mistralai-mistral-nemo-9330-v112-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v112-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v112-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v112
mistralai-mistral-nemo-9330-v112-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v112/config.json
mistralai-mistral-nemo-9330-v112-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v112/special_tokens_map.json
mistralai-mistral-nemo-9330-v112-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v112/tokenizer_config.json
mistralai-mistral-nemo-9330-v112-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v112/tokenizer.json
mistralai-mistral-nemo-9330-v112-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v112/flywheel_model.0.safetensors
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Job mistralai-mistral-nemo-9330-v112-mkmlizer completed after 114.06s with status: succeeded
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Inference service mistralai-mistral-nemo-9330-v112 ready after 230.80740785598755s
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Received healthy response to inference request in 2.473724603652954s
Received healthy response to inference request in 2.847679376602173s
Received healthy response to inference request in 1.9851372241973877s
Received healthy response to inference request in 2.2131733894348145s
Failed to get response for submission chaiml-elo-alignment-run-3_v36: ('http://chaiml-elo-alignment-run-3-v36-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:43380->127.0.0.1:8080: read: connection reset by peer\n')
Received healthy response to inference request in 1.961583137512207s
5 requests
0 failed requests
5th percentile: 1.966293954849243
10th percentile: 1.9710047721862793
20th percentile: 1.9804264068603517
30th percentile: 2.030744457244873
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70th percentile: 2.4216143608093263
80th percentile: 2.548515558242798
90th percentile: 2.6980974674224854
95th percentile: 2.772888422012329
99th percentile: 2.8327211856842043
mean time: 2.296259546279907
Pipeline stage StressChecker completed in 12.45s
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Inference service mistralai-mistral-nemo-9330-v112-profiler ready after 220.50378465652466s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/mistralai-mistral-nee5503f46f592762c68449400192c5591-deplodv7dl:/code/chaiverse_profiler_1727377526 --namespace tenant-chaiml-guanaco
kubectl exec -it mistralai-mistral-nee5503f46f592762c68449400192c5591-deplodv7dl --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727377526 && 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_1727377526/summary.json'
kubectl exec -it mistralai-mistral-nee5503f46f592762c68449400192c5591-deplodv7dl --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727377526/summary.json'
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