submission_id: riverise-mistral-0920-7872_v2
developer_uid: Riverise
best_of: 8
celo_rating: 1254.28
display_name: riverise-mistral-0920-7872_v1
family_friendly_score: 0.5421969957573674
family_friendly_standard_error: 0.00920697587356578
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': 0.7, 'top_p': 0.95, 'min_p': 0.05, 'top_k': 80, '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}
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: Riverise/mistral_0920_7872
latencies: [{'batch_size': 1, 'throughput': 0.6107471036799089, 'latency_mean': 1.6372385454177856, 'latency_p50': 1.6331278085708618, 'latency_p90': 1.8041443824768066}, {'batch_size': 3, 'throughput': 1.0872530653064958, 'latency_mean': 2.75314617395401, 'latency_p50': 2.7517426013946533, 'latency_p90': 3.026814270019531}, {'batch_size': 5, 'throughput': 1.2327482331599087, 'latency_mean': 4.038846219778061, 'latency_p50': 4.033775448799133, 'latency_p90': 4.508857464790344}, {'batch_size': 6, 'throughput': 1.2482472960913702, 'latency_mean': 4.778163821697235, 'latency_p50': 4.784634947776794, 'latency_p90': 5.379951739311219}, {'batch_size': 8, 'throughput': 1.2431755251359748, 'latency_mean': 6.401383904218673, 'latency_p50': 6.4418113231658936, 'latency_p90': 7.196049189567566}, {'batch_size': 10, 'throughput': 1.2072827579783132, 'latency_mean': 8.225046372413635, 'latency_p50': 8.33280873298645, 'latency_p90': 9.28163480758667}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: Riverise/mistral_0920_78
model_name: riverise-mistral-0920-7872_v1
model_num_parameters: 12772070400.0
model_repo: Riverise/mistral_0920_7872
model_size: 13B
num_battles: 2916
num_wins: 1460
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.21
timestamp: 2024-09-25T08:39:30+00:00
us_pacific_date: 2024-09-25
win_ratio: 0.5006858710562414
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name riverise-mistral-0920-7872-v2-mkmlizer
Waiting for job on riverise-mistral-0920-7872-v2-mkmlizer to finish
riverise-mistral-0920-7872-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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riverise-mistral-0920-7872-v2-mkmlizer: ║ /___/ ║
riverise-mistral-0920-7872-v2-mkmlizer: ║ ║
riverise-mistral-0920-7872-v2-mkmlizer: ║ Version: 0.11.12 ║
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riverise-mistral-0920-7872-v2-mkmlizer: ║ https://mk1.ai ║
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riverise-mistral-0920-7872-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
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riverise-mistral-0920-7872-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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riverise-mistral-0920-7872-v2-mkmlizer: quantized model in 35.729s
riverise-mistral-0920-7872-v2-mkmlizer: Processed model Riverise/mistral_0920_7872 in 80.292s
riverise-mistral-0920-7872-v2-mkmlizer: creating bucket guanaco-mkml-models
riverise-mistral-0920-7872-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
riverise-mistral-0920-7872-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/riverise-mistral-0920-7872-v2
riverise-mistral-0920-7872-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/riverise-mistral-0920-7872-v2/special_tokens_map.json
riverise-mistral-0920-7872-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/riverise-mistral-0920-7872-v2/config.json
riverise-mistral-0920-7872-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/riverise-mistral-0920-7872-v2/tokenizer_config.json
riverise-mistral-0920-7872-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/riverise-mistral-0920-7872-v2/tokenizer.json
riverise-mistral-0920-7872-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/riverise-mistral-0920-7872-v2/flywheel_model.0.safetensors
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Job riverise-mistral-0920-7872-v2-mkmlizer completed after 105.15s with status: succeeded
Stopping job with name riverise-mistral-0920-7872-v2-mkmlizer
Pipeline stage MKMLizer completed in 106.24s
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Creating inference service riverise-mistral-0920-7872-v2
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Inference service riverise-mistral-0920-7872-v2 ready after 212.18562865257263s
Pipeline stage MKMLDeployer completed in 212.54s
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Running pipeline stage StressChecker
Received healthy response to inference request in 3.2879719734191895s
Received healthy response to inference request in 2.3835458755493164s
Received healthy response to inference request in 2.1754584312438965s
Received healthy response to inference request in 2.750760793685913s
Received healthy response to inference request in 1.9223580360412598s
5 requests
0 failed requests
5th percentile: 1.972978115081787
10th percentile: 2.0235981941223145
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30th percentile: 2.2170759201049806
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60th percentile: 2.530431842803955
70th percentile: 2.6773178100585935
80th percentile: 2.8582030296325684
90th percentile: 3.0730875015258787
95th percentile: 3.180529737472534
99th percentile: 3.2664835262298584
mean time: 2.504019021987915
Pipeline stage StressChecker completed in 15.99s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 6.29s
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Creating inference service riverise-mistral-0920-7872-v2-profiler
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Inference service riverise-mistral-0920-7872-v2-profiler ready after 210.55080819129944s
Pipeline stage MKMLProfilerDeployer completed in 210.89s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/riverise-mistral-09269a10d211973fa955e61947bc5683a85-deplot95rx:/code/chaiverse_profiler_1727254171 --namespace tenant-chaiml-guanaco
kubectl exec -it riverise-mistral-09269a10d211973fa955e61947bc5683a85-deplot95rx --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1727254171 && 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_1727254171/summary.json'
kubectl exec -it riverise-mistral-09269a10d211973fa955e61947bc5683a85-deplot95rx --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1727254171/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1166.17s
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Checking if service riverise-mistral-0920-7872-v2-profiler is running
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Service riverise-mistral-0920-7872-v2-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.30s
Shutdown handler de-registered
riverise-mistral-0920-7872_v2 status is now inactive due to auto deactivation removed underperforming models
riverise-mistral-0920-7872_v2 status is now torndown due to DeploymentManager action