submission_id: mistralai-mistral-nemo_9330_v119
developer_uid: immaculate_possum_03470
best_of: 8
celo_rating: 1242.18
display_name: nemo_base_1
family_friendly_score: 0.5532742887815352
family_friendly_standard_error: 0.008124896444894846
formatter: {'memory_template': '<|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.2, 'top_k': 50, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n\n', '\nYou:', '[/INST]', '<|im_end|>', '</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': 0.6186135134722525, 'latency_mean': 1.6164512753486633, 'latency_p50': 1.6016021966934204, 'latency_p90': 1.7943617820739746}, {'batch_size': 3, 'throughput': 1.0831754020400342, 'latency_mean': 2.761759035587311, 'latency_p50': 2.7520241737365723, 'latency_p90': 3.073200011253357}, {'batch_size': 5, 'throughput': 1.2295071617302153, 'latency_mean': 4.045368403196335, 'latency_p50': 4.052712559700012, 'latency_p90': 4.566710710525513}, {'batch_size': 6, 'throughput': 1.2451172487779192, 'latency_mean': 4.790165674686432, 'latency_p50': 4.8483957052230835, 'latency_p90': 5.370291900634766}, {'batch_size': 8, 'throughput': 1.2449925795702048, 'latency_mean': 6.39738116145134, 'latency_p50': 6.4466869831085205, 'latency_p90': 7.275425410270691}, {'batch_size': 10, 'throughput': 1.1977863012344458, 'latency_mean': 8.29344957590103, 'latency_p50': 8.34026026725769, 'latency_p90': 9.344583702087402}]
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: 3838
num_wins: 1850
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.21
timestamp: 2024-09-26T22:27:44+00:00
us_pacific_date: 2024-09-26
win_ratio: 0.4820218863991662
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Running pipeline stage MKMLizer
Starting job with name mistralai-mistral-nemo-9330-v119-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v119-mkmlizer to finish
mistralai-mistral-nemo-9330-v119-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ _____ __ __ ║
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mistralai-mistral-nemo-9330-v119-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ /___/ ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ Version: 0.11.12 ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ https://mk1.ai ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ The license key for the current software has been verified as ║
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mistralai-mistral-nemo-9330-v119-mkmlizer: ║ Chai Research Corp. ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ║ ║
mistralai-mistral-nemo-9330-v119-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v119-mkmlizer: Downloaded to shared memory in 58.326s
mistralai-mistral-nemo-9330-v119-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp5rzvc_gr, device:0
mistralai-mistral-nemo-9330-v119-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v119-mkmlizer: quantized model in 35.591s
mistralai-mistral-nemo-9330-v119-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 93.917s
mistralai-mistral-nemo-9330-v119-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v119-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v119-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v119
mistralai-mistral-nemo-9330-v119-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v119/config.json
mistralai-mistral-nemo-9330-v119-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v119/special_tokens_map.json
mistralai-mistral-nemo-9330-v119-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v119/tokenizer_config.json
mistralai-mistral-nemo-9330-v119-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v119/flywheel_model.0.safetensors
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/mistralai-mistral-ne4e6961e0d6d70632be6377864c75a56c-deplokl8fx:/code/chaiverse_profiler_1727390332 --namespace tenant-chaiml-guanaco
kubectl exec -it mistralai-mistral-ne4e6961e0d6d70632be6377864c75a56c-deplokl8fx --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727390332 && 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_1727390332/summary.json'
kubectl exec -it mistralai-mistral-ne4e6961e0d6d70632be6377864c75a56c-deplokl8fx --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727390332/summary.json'
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Running pipeline stage MKMLDeleter
Deleting key mistralai-mistral-nemo-9330-v116/special_tokens_map.json from bucket guanaco-mkml-models
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Cleaning model data from model cache
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Pipeline stage MKMLModelDeleter completed in 27.95s
Shutdown handler not registered because Python interpreter is not running in the main thread
Checking if service mistralai-mistral-nemo-9330-v123 is running
Cleaning model data from S3
admin requested tearing down of mistralai-mistral-nemo_9330_v128
Running pipeline stage MKMLModelDeleter
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