cgato-nemo-12b-theanswer_4750

developer_uid: c.gato

submission_id: cgato-nemo-12b-theanswer_4750_v1

model_name: cgato-nemo-12b-theanswer_4750_v1

model_group: cgato/Nemo-12b-TheAnswer

status: inactive

timestamp: 2024-11-21T05:57:07+00:00

num_battles: 11688

num_wins: 5917

celo_rating: 1254.68

family_friendly_score: 0.562

family_friendly_standard_error: 0.00701649485141976

submission_type: basic

model_repo: cgato/Nemo-12b-TheAnswer-v0.1-E2

model_architecture: MistralForCausalLM

model_num_parameters: 12772111360.0

best_of: 8

max_input_tokens: 1024

max_output_tokens: 64

latencies: [{'batch_size': 1, 'throughput': 0.6282567665146206, 'latency_mean': 1.5916428077220917, 'latency_p50': 1.5991894006729126, 'latency_p90': 1.7649943113327027}, {'batch_size': 3, 'throughput': 1.1506223598976544, 'latency_mean': 2.5931037962436676, 'latency_p50': 2.602343797683716, 'latency_p90': 2.811353325843811}, {'batch_size': 5, 'throughput': 1.4005584123210448, 'latency_mean': 3.5503133654594423, 'latency_p50': 3.5425819158554077, 'latency_p90': 3.9849804162979128}, {'batch_size': 6, 'throughput': 1.488792313081164, 'latency_mean': 4.020002077817917, 'latency_p50': 4.0141884088516235, 'latency_p90': 4.500082159042358}, {'batch_size': 8, 'throughput': 1.5650723732686624, 'latency_mean': 5.068063514232636, 'latency_p50': 5.034111142158508, 'latency_p90': 5.6724780082702635}, {'batch_size': 10, 'throughput': 1.5960920938361522, 'latency_mean': 6.215891019105912, 'latency_p50': 6.205859303474426, 'latency_p90': 7.117577934265136}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: cgato-nemo-12b-theanswer_4750_v1

is_internal_developer: False

language_model: cgato/Nemo-12b-TheAnswer-v0.1-E2

model_size: 13B

ranking_group: single

throughput_3p7s: 1.44

us_pacific_date: 2024-11-20

win_ratio: 0.5062457221081451

generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}

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': True}

Resubmit model

Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name cgato-nemo-12b-theanswer-4750-v1-mkmlizer
Waiting for job on cgato-nemo-12b-theanswer-4750-v1-mkmlizer to finish
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║     _____            __           __                                ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║       /___/                                                         ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║                                                                     ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  https://mk1.ai                                                     ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║                                                                     ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  belonging to:                                                      ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║                                                                     ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  Chai Research Corp.                                                ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ║                                                                     ║
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: Downloaded to shared memory in 47.190s
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpfiost6io, device:0
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: quantized model in 35.375s
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: Processed model cgato/Nemo-12b-TheAnswer-v0.1-E2 in 82.565s
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: creating bucket guanaco-mkml-models
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cgato-nemo-12b-theanswer-4750-v1
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cgato-nemo-12b-theanswer-4750-v1/special_tokens_map.json
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cgato-nemo-12b-theanswer-4750-v1/config.json
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cgato-nemo-12b-theanswer-4750-v1/tokenizer_config.json
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cgato-nemo-12b-theanswer-4750-v1/tokenizer.json
cgato-nemo-12b-theanswer-4750-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cgato-nemo-12b-theanswer-4750-v1/flywheel_model.0.safetensors
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Job cgato-nemo-12b-theanswer-4750-v1-mkmlizer completed after 104.31s with status: succeeded
Stopping job with name cgato-nemo-12b-theanswer-4750-v1-mkmlizer
Pipeline stage MKMLizer completed in 105.02s
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Pipeline stage MKMLTemplater completed in 0.16s
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Creating inference service cgato-nemo-12b-theanswer-4750-v1
Waiting for inference service cgato-nemo-12b-theanswer-4750-v1 to be ready
Inference service cgato-nemo-12b-theanswer-4750-v1 ready after 261.95727729797363s
Pipeline stage MKMLDeployer completed in 262.58s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.1480419635772705s
Received healthy response to inference request in 1.668555498123169s
Received healthy response to inference request in 1.790764331817627s
Received healthy response to inference request in 1.7763733863830566s
Received healthy response to inference request in 1.9461557865142822s
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