developer_uid: zonemercy
submission_id: zonemercy-base-story-v1_v4
model_name: 0906stv1-0
model_group: zonemercy/Base-Story-v1
status: torndown
timestamp: 2024-09-06T12:35:43+00:00
num_battles: 10820
num_wins: 2444
celo_rating: 1014.54
family_friendly_score: 0.0
submission_type: basic
model_repo: zonemercy/Base-Story-v1
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 2
max_input_tokens: 1024
max_output_tokens: 128
latencies: [{'batch_size': 1, 'throughput': 0.36502631750601877, 'latency_mean': 2.7394697523117064, 'latency_p50': 2.723710536956787, 'latency_p90': 2.9011370182037353}, {'batch_size': 3, 'throughput': 0.847294809817899, 'latency_mean': 3.532529106140137, 'latency_p50': 3.5369362831115723, 'latency_p90': 3.7784530401229857}, {'batch_size': 5, 'throughput': 1.180642741317926, 'latency_mean': 4.205241639614105, 'latency_p50': 4.204171419143677, 'latency_p90': 4.470502543449402}, {'batch_size': 6, 'throughput': 1.3007253806363295, 'latency_mean': 4.5650761556625366, 'latency_p50': 4.559537649154663, 'latency_p90': 4.951426672935486}, {'batch_size': 8, 'throughput': 1.4920952201803481, 'latency_mean': 5.314340997934341, 'latency_p50': 5.310624480247498, 'latency_p90': 5.799722456932068}, {'batch_size': 10, 'throughput': 1.593402433537245, 'latency_mean': 6.216106929779053, 'latency_p50': 6.245798349380493, 'latency_p90': 6.778781914710999}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: 0906stv1-0
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: zonemercy/Base-Story-v1
model_size: 13B
ranking_group: single
throughput_3p7s: 0.95
us_pacific_date: 2024-09-06
win_ratio: 0.22587800369685768
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.05, 'top_k': 100, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['</s>', 'Bot:', 'User:', 'You:'], 'max_input_tokens': 1024, 'best_of': 2, 'max_output_tokens': 128}
formatter: {'memory_template': " Write a slice of story that takes place over the course of a single day in Bot's life. Use stream-of-consciousness narration to explore the character's thoughts and perceptions. Include poetic, impressionistic descriptions of the character's surroundings and sensations. Weave in memories and reflections that provide insight into the Bot's past and inner life. The scene should feel like part of a lived-in world, with the scene naturally existing in a wider story.\n Bot's Name: {bot_name}\nBot's Persona: {memory}\n####\n ", 'prompt_template': '', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot[Start story]:', 'truncate_by_message': False}
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 zonemercy-base-story-v1-v4-mkmlizer
Waiting for job on zonemercy-base-story-v1-v4-mkmlizer to finish
zonemercy-base-story-v1-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
zonemercy-base-story-v1-v4-mkmlizer: ║     _____            __           __                                ║
zonemercy-base-story-v1-v4-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
zonemercy-base-story-v1-v4-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
zonemercy-base-story-v1-v4-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
zonemercy-base-story-v1-v4-mkmlizer: ║       /___/                                                         ║
zonemercy-base-story-v1-v4-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v4-mkmlizer: ║  Version: 0.10.1                                                    ║
zonemercy-base-story-v1-v4-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
zonemercy-base-story-v1-v4-mkmlizer: ║  https://mk1.ai                                                     ║
zonemercy-base-story-v1-v4-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v4-mkmlizer: ║  The license key for the current software has been verified as      ║
zonemercy-base-story-v1-v4-mkmlizer: ║  belonging to:                                                      ║
zonemercy-base-story-v1-v4-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v4-mkmlizer: ║  Chai Research Corp.                                                ║
zonemercy-base-story-v1-v4-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
zonemercy-base-story-v1-v4-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
zonemercy-base-story-v1-v4-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Failed to get response for submission zonemercy-base-story-v1_v3: ('http://zonemercy-base-story-v1-v3-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-lexical-nemo-_1518_v23: ('http://zonemercy-lexical-nemo-1518-v23-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v3: ('http://zonemercy-base-story-v1-v3-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'upstream connect error or disconnect/reset before headers. reset reason: connection timeout')
zonemercy-base-story-v1-v4-mkmlizer: Downloaded to shared memory in 57.502s
zonemercy-base-story-v1-v4-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpdqn0b86b, device:0
zonemercy-base-story-v1-v4-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Failed to get response for submission zonemercy-base-story-v1_v2: ('http://zonemercy-base-story-v1-v2-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
zonemercy-base-story-v1-v4-mkmlizer: quantized model in 40.971s
zonemercy-base-story-v1-v4-mkmlizer: Processed model zonemercy/Base-Story-v1 in 98.473s
zonemercy-base-story-v1-v4-mkmlizer: creating bucket guanaco-mkml-models
zonemercy-base-story-v1-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
zonemercy-base-story-v1-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/zonemercy-base-story-v1-v4
zonemercy-base-story-v1-v4-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v4/config.json
zonemercy-base-story-v1-v4-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v4/special_tokens_map.json
zonemercy-base-story-v1-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v4/tokenizer_config.json
zonemercy-base-story-v1-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v4/tokenizer.json
zonemercy-base-story-v1-v4-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/zonemercy-base-story-v1-v4/flywheel_model.0.safetensors
zonemercy-base-story-v1-v4-mkmlizer: 
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Job zonemercy-base-story-v1-v4-mkmlizer completed after 125.31s with status: succeeded
Stopping job with name zonemercy-base-story-v1-v4-mkmlizer
Pipeline stage MKMLizer completed in 126.12s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.09s
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Running pipeline stage MKMLDeployer
Creating inference service zonemercy-base-story-v1-v4
Waiting for inference service zonemercy-base-story-v1-v4 to be ready
Failed to get response for submission zonemercy-base-story-v1_v3: ('http://zonemercy-base-story-v1-v3-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v3: ('http://zonemercy-base-story-v1-v3-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Failed to get response for submission zonemercy-lexical-nemo-_1518_v23: ('http://zonemercy-lexical-nemo-1518-v23-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v2: ('http://zonemercy-base-story-v1-v2-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Inference service zonemercy-base-story-v1-v4 ready after 150.3810477256775s
Pipeline stage MKMLDeployer completed in 150.94s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.1192731857299805s
Received healthy response to inference request in 3.0356998443603516s
Received healthy response to inference request in 3.4782874584198s
Received healthy response to inference request in 3.0319058895111084s
Received healthy response to inference request in 3.4067037105560303s
5 requests
0 failed requests
5th percentile: 3.032664680480957
10th percentile: 3.0334234714508055
20th percentile: 3.034941053390503
30th percentile: 3.0524145126342774
40th percentile: 3.0858438491821287
50th percentile: 3.1192731857299805
60th percentile: 3.2342453956604005
70th percentile: 3.34921760559082
80th percentile: 3.4210204601287844
90th percentile: 3.449653959274292
95th percentile: 3.4639707088470457
99th percentile: 3.475424108505249
mean time: 3.2143740177154543
Pipeline stage StressChecker completed in 17.47s
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Running pipeline stage TriggerMKMLProfilingPipeline
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Pipeline stage TriggerMKMLProfilingPipeline completed in 4.61s
Shutdown handler de-registered
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Pipeline stage MKMLProfilerTemplater completed in 0.12s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service zonemercy-base-story-v1-v4-profiler
Waiting for inference service zonemercy-base-story-v1-v4-profiler to be ready
Inference service zonemercy-base-story-v1-v4-profiler ready after 150.33212304115295s
Pipeline stage MKMLProfilerDeployer completed in 150.71s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/zonemercy-base-story-v1-v4-profiler-predictor-00001-deploykpkrs:/code/chaiverse_profiler_1725626636 --namespace tenant-chaiml-guanaco
kubectl exec -it zonemercy-base-story-v1-v4-profiler-predictor-00001-deploykpkrs --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725626636 && python profiles.py profile --best_of_n 2 --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 128 --summary /code/chaiverse_profiler_1725626636/summary.json'
kubectl exec -it zonemercy-base-story-v1-v4-profiler-predictor-00001-deploykpkrs --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725626636/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1374.13s
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Running pipeline stage MKMLProfilerDeleter
Checking if service zonemercy-base-story-v1-v4-profiler is running
Tearing down inference service zonemercy-base-story-v1-v4-profiler
Service zonemercy-base-story-v1-v4-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.66s
Shutdown handler de-registered
zonemercy-base-story-v1_v4 status is now inactive due to auto deactivation removed underperforming models
Running pipeline stage MKMLDeleter
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Cleaning model data from model cache
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Cleaning model data from S3
Cleaning model data from model cache
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Shutdown handler not registered because Python interpreter is not running in the main thread
Cleaning model data from model cache
admin requested tearing down of zonemercy-base-story-v1_v4
Checking if service trace2333-mistral-trial6-v6 is running
Running pipeline stage MKMLDeleter
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Cleaning model data from model cache
Running pipeline stage MKMLModelDeleter
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Shutdown handler not registered because Python interpreter is not running in the main thread
Cleaning model data from S3
Checking if service zonemercy-base-story-v1-v1 is running
admin requested tearing down of zonemercy-base-story-v1_v5
Running pipeline stage MKMLDeleter
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Tearing down inference service trace2333-mistral-trial6-v2
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Cleaning model data from S3
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