submission_id: trace2333-mistral-trial6_v2
developer_uid: Trace2333
alignment_samples: 9711
alignment_score: -0.38295837321576404
best_of: 8
celo_rating: 1258.33
display_name: trace2333-mistral-trial6_v2
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': 0.9, 'top_p': 1.0, 'min_p': 0.06, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>', '###'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: Trace2333/mistral_trial6
latencies: [{'batch_size': 1, 'throughput': 0.6918249864968032, 'latency_mean': 1.4453961873054504, 'latency_p50': 1.4497231245040894, 'latency_p90': 1.6045588731765748}, {'batch_size': 3, 'throughput': 1.33459401856042, 'latency_mean': 2.245481617450714, 'latency_p50': 2.24993097782135, 'latency_p90': 2.475707936286926}, {'batch_size': 5, 'throughput': 1.5608616518961982, 'latency_mean': 3.1817048990726473, 'latency_p50': 3.1689677238464355, 'latency_p90': 3.597099447250366}, {'batch_size': 6, 'throughput': 1.6453841092247163, 'latency_mean': 3.612380130290985, 'latency_p50': 3.645266532897949, 'latency_p90': 4.146953368186951}, {'batch_size': 8, 'throughput': 1.6323508234785236, 'latency_mean': 4.869166822433471, 'latency_p50': 4.886404275894165, 'latency_p90': 5.590156984329224}, {'batch_size': 10, 'throughput': 1.5478300231099846, 'latency_mean': 6.421971708536148, 'latency_p50': 6.4519267082214355, 'latency_p90': 7.2702796459198}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: Trace2333/mistral_trial6
model_name: trace2333-mistral-trial6_v2
model_num_parameters: 12772070400.0
model_repo: Trace2333/mistral_trial6
model_size: 13B
num_battles: 9711
num_wins: 5379
propriety_score: 0.7565217391304347
propriety_total_count: 1035.0
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.66
timestamp: 2024-09-06T12:38:20+00:00
us_pacific_date: 2024-09-06
win_ratio: 0.5539079394501081
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name trace2333-mistral-trial6-v2-mkmlizer
Waiting for job on trace2333-mistral-trial6-v2-mkmlizer to finish
trace2333-mistral-trial6-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
trace2333-mistral-trial6-v2-mkmlizer: ║ _____ __ __ ║
trace2333-mistral-trial6-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
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trace2333-mistral-trial6-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
trace2333-mistral-trial6-v2-mkmlizer: ║ /___/ ║
trace2333-mistral-trial6-v2-mkmlizer: ║ ║
trace2333-mistral-trial6-v2-mkmlizer: ║ Version: 0.10.1 ║
trace2333-mistral-trial6-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
trace2333-mistral-trial6-v2-mkmlizer: ║ https://mk1.ai ║
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trace2333-mistral-trial6-v2-mkmlizer: ║ The license key for the current software has been verified as ║
trace2333-mistral-trial6-v2-mkmlizer: ║ belonging to: ║
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trace2333-mistral-trial6-v2-mkmlizer: ║ Chai Research Corp. ║
trace2333-mistral-trial6-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
trace2333-mistral-trial6-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
trace2333-mistral-trial6-v2-mkmlizer: ║ ║
trace2333-mistral-trial6-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
trace2333-mistral-trial6-v2-mkmlizer: Downloaded to shared memory in 29.482s
trace2333-mistral-trial6-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmplh52vinv, device:0
trace2333-mistral-trial6-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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')
trace2333-mistral-trial6-v2-mkmlizer: quantized model in 36.193s
trace2333-mistral-trial6-v2-mkmlizer: Processed model Trace2333/mistral_trial6 in 65.675s
trace2333-mistral-trial6-v2-mkmlizer: creating bucket guanaco-mkml-models
trace2333-mistral-trial6-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
trace2333-mistral-trial6-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/trace2333-mistral-trial6-v2
trace2333-mistral-trial6-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/trace2333-mistral-trial6-v2/config.json
trace2333-mistral-trial6-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/trace2333-mistral-trial6-v2/special_tokens_map.json
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\')]"}')
trace2333-mistral-trial6-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/trace2333-mistral-trial6-v2/flywheel_model.0.safetensors
trace2333-mistral-trial6-v2-mkmlizer: Loading 0: 0%| | 0/363 [00:00<?, ?it/s] Loading 0: 2%|▏ | 7/363 [00:00<00:07, 48.59it/s] Loading 0: 5%|▍ | 17/363 [00:00<00:04, 74.12it/s] Loading 0: 7%|▋ | 25/363 [00:00<00:04, 70.47it/s] Loading 0: 10%|▉ | 35/363 [00:00<00:04, 80.76it/s] Loading 0: 12%|█▏ | 44/363 [00:00<00:03, 83.06it/s] Loading 0: 15%|█▍ | 53/363 [00:00<00:03, 82.49it/s] Loading 0: 17%|█▋ | 62/363 [00:01<00:15, 19.84it/s] Loading 0: 19%|█▉ | 70/363 [00:01<00:11, 24.57it/s] Loading 0: 22%|██▏ | 79/363 [00:02<00:08, 31.98it/s] Loading 0: 24%|██▍ | 88/363 [00:02<00:06, 39.73it/s] Loading 0: 27%|██▋ | 97/363 [00:02<00:05, 45.81it/s] Loading 0: 29%|██▉ | 106/363 [00:02<00:04, 53.41it/s] Loading 0: 32%|███▏ | 115/363 [00:02<00:04, 57.82it/s] Loading 0: 34%|███▍ | 124/363 [00:02<00:03, 60.66it/s] Loading 0: 37%|███▋ | 133/363 [00:02<00:03, 65.64it/s] Loading 0: 39%|███▉ | 142/363 [00:03<00:10, 20.17it/s] Loading 0: 42%|████▏ | 151/363 [00:04<00:08, 26.06it/s] Loading 0: 44%|████▍ | 160/363 [00:04<00:06, 32.86it/s] Loading 0: 48%|████▊ | 175/363 [00:04<00:04, 46.19it/s] Loading 0: 52%|█████▏ | 187/363 [00:04<00:03, 53.90it/s] Loading 0: 54%|█████▍ | 196/363 [00:04<00:03, 55.31it/s] Loading 0: 56%|█████▋ | 205/363 [00:04<00:02, 58.04it/s] Loading 0: 59%|█████▉ | 214/363 [00:04<00:02, 59.52it/s] Loading 0: 61%|██████▏ | 223/363 [00:06<00:06, 20.19it/s] Loading 0: 64%|██████▍ | 232/363 [00:06<00:05, 25.64it/s] Loading 0: 66%|██████▋ | 241/363 [00:06<00:03, 31.26it/s] Loading 0: 69%|██████▉ | 250/363 [00:06<00:02, 37.86it/s] Loading 0: 71%|███████▏ | 259/363 [00:06<00:02, 44.08it/s] Loading 0: 74%|███████▍ | 268/363 [00:06<00:01, 51.30it/s] Loading 0: 76%|███████▋ | 277/363 [00:06<00:01, 53.00it/s] Loading 0: 79%|███████▉ | 286/363 [00:06<00:01, 57.07it/s] Loading 0: 81%|████████▏ | 295/363 [00:07<00:01, 62.17it/s] Loading 0: 84%|████████▎ | 304/363 [00:08<00:02, 19.86it/s] Loading 0: 86%|████████▌ | 313/363 [00:08<00:01, 25.52it/s] Loading 0: 89%|████████▊ | 322/363 [00:08<00:01, 32.13it/s] Loading 0: 91%|█████████ | 331/363 [00:08<00:00, 39.24it/s] Loading 0: 94%|█████████▎| 340/363 [00:08<00:00, 45.54it/s] Loading 0: 96%|█████████▌| 349/363 [00:08<00:00, 51.26it/s] Loading 0: 99%|█████████▊| 358/363 [00:08<00:00, 57.86it/s]
Job trace2333-mistral-trial6-v2-mkmlizer completed after 84.71s with status: succeeded
Stopping job with name trace2333-mistral-trial6-v2-mkmlizer
Pipeline stage MKMLizer completed in 85.78s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.08s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service trace2333-mistral-trial6-v2
Waiting for inference service trace2333-mistral-trial6-v2 to be ready
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\')]"}')
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\')]"}')
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')
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\')]"}')
Inference service trace2333-mistral-trial6-v2 ready after 150.4540774822235s
Pipeline stage MKMLDeployer completed in 150.83s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.1840617656707764s
Received healthy response to inference request in 1.4000179767608643s
Received healthy response to inference request in 2.45613694190979s
Received healthy response to inference request in 1.6792035102844238s
Received healthy response to inference request in 1.6128668785095215s
5 requests
0 failed requests
5th percentile: 1.4425877571105956
10th percentile: 1.4851575374603272
20th percentile: 1.5702970981597901
30th percentile: 1.626134204864502
40th percentile: 1.6526688575744628
50th percentile: 1.6792035102844238
60th percentile: 1.8811468124389648
70th percentile: 2.0830901145935057
80th percentile: 2.2384768009185794
90th percentile: 2.3473068714141845
95th percentile: 2.401721906661987
99th percentile: 2.4452539348602294
mean time: 1.8664574146270752
Pipeline stage StressChecker completed in 10.06s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
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')
Pipeline stage TriggerMKMLProfilingPipeline completed in 5.65s
Shutdown handler de-registered
trace2333-mistral-trial6_v2 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.10s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service trace2333-mistral-trial6-v2-profiler
Waiting for inference service trace2333-mistral-trial6-v2-profiler to be ready
Inference service trace2333-mistral-trial6-v2-profiler ready after 150.34704875946045s
Pipeline stage MKMLProfilerDeployer completed in 150.68s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/trace2333-mistral-trial6-v2-profiler-predictor-00001-deplomngkf:/code/chaiverse_profiler_1725626735 --namespace tenant-chaiml-guanaco
kubectl exec -it trace2333-mistral-trial6-v2-profiler-predictor-00001-deplomngkf --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725626735 && 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 512 --output_tokens 64 --summary /code/chaiverse_profiler_1725626735/summary.json'
kubectl exec -it trace2333-mistral-trial6-v2-profiler-predictor-00001-deplomngkf --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725626735/summary.json'
Pipeline stage MKMLProfilerRunner completed in 945.48s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service trace2333-mistral-trial6-v2-profiler is running
Tearing down inference service trace2333-mistral-trial6-v2-profiler
Service trace2333-mistral-trial6-v2-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.66s
Shutdown handler de-registered
trace2333-mistral-trial6_v2 status is now inactive due to auto deactivation removed underperforming models

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