submission_id: rica40325-mistral-13b-2452_v3
developer_uid: rica40325
best_of: 8
celo_rating: 1258.34
display_name: rica40325-mistral-13b-2452_v1
family_friendly_score: 0.5585982382229031
family_friendly_standard_error: 0.009691209730151603
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': 0.95, 'top_p': 0.95, 'min_p': 0.05, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['</s>', 'Bot:', 'User:', 'You:', 'Me:', '####'], '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: rica40325/mistral-13B-2452
latencies: [{'batch_size': 1, 'throughput': 0.616917987062348, 'latency_mean': 1.6208806943893432, 'latency_p50': 1.6192967891693115, 'latency_p90': 1.7898290157318115}, {'batch_size': 3, 'throughput': 1.0944451840314815, 'latency_mean': 2.7280071783065796, 'latency_p50': 2.726317048072815, 'latency_p90': 3.120296764373779}, {'batch_size': 5, 'throughput': 1.249175210241515, 'latency_mean': 3.987939409017563, 'latency_p50': 3.980242609977722, 'latency_p90': 4.567053484916687}, {'batch_size': 6, 'throughput': 1.2689309397572623, 'latency_mean': 4.705543678998947, 'latency_p50': 4.724991798400879, 'latency_p90': 5.245417213439941}, {'batch_size': 8, 'throughput': 1.2638193194785556, 'latency_mean': 6.30363161444664, 'latency_p50': 6.413603901863098, 'latency_p90': 6.966267991065979}, {'batch_size': 10, 'throughput': 1.2246012524987653, 'latency_mean': 8.125067225694657, 'latency_p50': 8.152233362197876, 'latency_p90': 9.10272512435913}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: rica40325/mistral-13B-24
model_name: rica40325-mistral-13b-2452_v1
model_num_parameters: 12772070400.0
model_repo: rica40325/mistral-13B-2452
model_size: 13B
num_battles: 2685
num_wins: 1371
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.23
timestamp: 2024-09-25T08:10:37+00:00
us_pacific_date: 2024-09-25
win_ratio: 0.5106145251396648
Resubmit model
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Running pipeline stage MKMLizer
Starting job with name rica40325-mistral-13b-2452-v3-mkmlizer
Waiting for job on rica40325-mistral-13b-2452-v3-mkmlizer to finish
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rica40325-mistral-13b-2452-v3-mkmlizer: ║     _____            __           __                                ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║       /___/                                                         ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║                                                                     ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  Version: 0.11.12                                                   ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  https://mk1.ai                                                     ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║                                                                     ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  belonging to:                                                      ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║                                                                     ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  Chai Research Corp.                                                ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
rica40325-mistral-13b-2452-v3-mkmlizer: ║                                                                     ║
rica40325-mistral-13b-2452-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
rica40325-mistral-13b-2452-v3-mkmlizer: Downloaded to shared memory in 29.157s
rica40325-mistral-13b-2452-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp8aea62vf, device:0
rica40325-mistral-13b-2452-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
rica40325-mistral-13b-2452-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py:55: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
rica40325-mistral-13b-2452-v3-mkmlizer:   tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
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rica40325-mistral-13b-2452-v3-mkmlizer: quantized model in 36.532s
rica40325-mistral-13b-2452-v3-mkmlizer: Processed model rica40325/mistral-13B-2452 in 65.690s
rica40325-mistral-13b-2452-v3-mkmlizer: creating bucket guanaco-mkml-models
rica40325-mistral-13b-2452-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rica40325-mistral-13b-2452-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rica40325-mistral-13b-2452-v3
rica40325-mistral-13b-2452-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rica40325-mistral-13b-2452-v3/config.json
rica40325-mistral-13b-2452-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rica40325-mistral-13b-2452-v3/special_tokens_map.json
rica40325-mistral-13b-2452-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rica40325-mistral-13b-2452-v3/tokenizer_config.json
rica40325-mistral-13b-2452-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rica40325-mistral-13b-2452-v3/tokenizer.json
rica40325-mistral-13b-2452-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/rica40325-mistral-13b-2452-v3/flywheel_model.0.safetensors
Job rica40325-mistral-13b-2452-v3-mkmlizer completed after 95.25s with status: succeeded
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Inference service rica40325-mistral-13b-2452-v3 ready after 212.6531002521515s
Pipeline stage MKMLDeployer completed in 214.27s
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Running pipeline stage StressChecker
Received healthy response to inference request in 6.606102466583252s
Received healthy response to inference request in 3.847417116165161s
Received healthy response to inference request in 5.133509635925293s
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Received healthy response to inference request in 2.693202018737793s
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20th percentile: 2.634477233886719
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99th percentile: 6.547198753356933
mean time: 4.135961866378784
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Received healthy response to inference request in 4.019929885864258s
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Received healthy response to inference request in 3.2996935844421387s
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5th percentile: 2.1313962936401367
10th percentile: 2.145883798599243
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30th percentile: 2.2096137046813964
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50th percentile: 2.2906832695007324
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90th percentile: 3.73183536529541
95th percentile: 3.875882625579834
99th percentile: 3.991120433807373
mean time: 2.783312368392944
Pipeline stage StressChecker completed in 40.38s
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Inference service rica40325-mistral-13b-2452-v3-profiler ready after 220.57646894454956s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/rica40325-mistral-13def8aacf8fb5f22ee1bdc94d68e47f6b-deploj2j7x:/code/chaiverse_profiler_1727252465 --namespace tenant-chaiml-guanaco
kubectl exec -it rica40325-mistral-13def8aacf8fb5f22ee1bdc94d68e47f6b-deploj2j7x --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727252465 && 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_1727252465/summary.json'
kubectl exec -it rica40325-mistral-13def8aacf8fb5f22ee1bdc94d68e47f6b-deploj2j7x --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727252465/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1152.90s
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admin requested tearing down of rica40325-mistral-13b-2452_v3
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rica40325-mistral-13b-2452_v3 status is now torndown due to DeploymentManager action