submission_id: cgato-nemo-12b-thespice-_3053_v2
developer_uid: c.gato
best_of: 8
celo_rating: 1257.92
display_name: cgato-nemo-12b-thespice-_3053_v2
family_friendly_score: 0.5671999999999999
family_friendly_standard_error: 0.007006913157732155
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}
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}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: cgato/Nemo-12b-TheSpice-V0.9-All-v2-KTO-v0.3-BigBoy-20k
latencies: [{'batch_size': 1, 'throughput': 0.603442064321151, 'latency_mean': 1.6570634949207306, 'latency_p50': 1.6480900049209595, 'latency_p90': 1.8403777122497558}, {'batch_size': 3, 'throughput': 1.0922144536960248, 'latency_mean': 2.7384584450721743, 'latency_p50': 2.7272297143936157, 'latency_p90': 3.051574873924255}, {'batch_size': 5, 'throughput': 1.304159393566678, 'latency_mean': 3.805332441329956, 'latency_p50': 3.7969138622283936, 'latency_p90': 4.247622871398926}, {'batch_size': 6, 'throughput': 1.3794625458154173, 'latency_mean': 4.329370688199997, 'latency_p50': 4.3261635303497314, 'latency_p90': 4.846419501304626}, {'batch_size': 8, 'throughput': 1.4409439619255304, 'latency_mean': 5.514404929876328, 'latency_p50': 5.531528115272522, 'latency_p90': 6.234166169166565}, {'batch_size': 10, 'throughput': 1.4785215324011702, 'latency_mean': 6.7112818169593815, 'latency_p50': 6.790502071380615, 'latency_p90': 7.51644549369812}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: cgato/Nemo-12b-TheSpice-
model_name: cgato-nemo-12b-thespice-_3053_v2
model_num_parameters: 12772121600.0
model_repo: cgato/Nemo-12b-TheSpice-V0.9-All-v2-KTO-v0.3-BigBoy-20k
model_size: 13B
num_battles: 18455
num_wins: 9658
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.3
timestamp: 2024-11-07T19:18:22+00:00
us_pacific_date: 2024-11-07
win_ratio: 0.5233270116499593
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-thespice-3053-v2-mkmlizer
Waiting for job on cgato-nemo-12b-thespice-3053-v2-mkmlizer to finish
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ _____ __ __ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ /___/ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ Version: 0.11.33 ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ https://mk1.ai ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ The license key for the current software has been verified as ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ belonging to: ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ Chai Research Corp. ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ Expiration: 2025-01-15 23:59:59 ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ║ ║
cgato-nemo-12b-thespice-3053-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Connection pool is full, discarding connection: %s. Connection pool size: %s
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cgato-nemo-12b-thespice-3053-v2-mkmlizer: Downloaded to shared memory in 42.704s
cgato-nemo-12b-thespice-3053-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpee1gik06, device:0
cgato-nemo-12b-thespice-3053-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cgato-nemo-12b-thespice-3053-v2-mkmlizer: quantized model in 36.273s
cgato-nemo-12b-thespice-3053-v2-mkmlizer: Processed model cgato/Nemo-12b-TheSpice-V0.9-All-v2-KTO-v0.3-BigBoy-20k in 78.977s
cgato-nemo-12b-thespice-3053-v2-mkmlizer: creating bucket guanaco-mkml-models
cgato-nemo-12b-thespice-3053-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cgato-nemo-12b-thespice-3053-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cgato-nemo-12b-thespice-3053-v2
cgato-nemo-12b-thespice-3053-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cgato-nemo-12b-thespice-3053-v2/config.json
cgato-nemo-12b-thespice-3053-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cgato-nemo-12b-thespice-3053-v2/special_tokens_map.json
cgato-nemo-12b-thespice-3053-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cgato-nemo-12b-thespice-3053-v2/tokenizer_config.json
cgato-nemo-12b-thespice-3053-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cgato-nemo-12b-thespice-3053-v2/tokenizer.json
cgato-nemo-12b-thespice-3053-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cgato-nemo-12b-thespice-3053-v2/flywheel_model.0.safetensors
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Job cgato-nemo-12b-thespice-3053-v2-mkmlizer completed after 104.33s with status: succeeded
Stopping job with name cgato-nemo-12b-thespice-3053-v2-mkmlizer
Pipeline stage MKMLizer completed in 104.81s
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Creating inference service cgato-nemo-12b-thespice-3053-v2
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Inference service cgato-nemo-12b-thespice-3053-v2 ready after 170.6225507259369s
Pipeline stage MKMLDeployer completed in 171.17s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.1795787811279297s
Received healthy response to inference request in 1.8608527183532715s
Received healthy response to inference request in 1.9514641761779785s
Received healthy response to inference request in 1.6593470573425293s
Received healthy response to inference request in 1.4811437129974365s
5 requests
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5th percentile: 1.516784381866455
10th percentile: 1.5524250507354735
20th percentile: 1.6237063884735108
30th percentile: 1.6996481895446778
40th percentile: 1.7802504539489745
50th percentile: 1.8608527183532715
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70th percentile: 1.933341884613037
80th percentile: 1.9970870971679688
90th percentile: 2.088332939147949
95th percentile: 2.1339558601379394
99th percentile: 2.170454196929932
mean time: 1.826477289199829
Pipeline stage StressChecker completed in 10.40s
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Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 2995.98s
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