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Running pipeline stage MKMLizer
Starting job with name rinen0721-mistral-dpo-0213-m3-v2-mkmlizer
Waiting for job on rinen0721-mistral-dpo-0213-m3-v2-mkmlizer to finish
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ _____ __ __ ║
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rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ /___/ ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ Version: 0.12.8 ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ https://mk1.ai ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ The license key for the current software has been verified as ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ belonging to: ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ Chai Research Corp. ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ Expiration: 2025-04-15 23:59:59 ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ║ ║
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: Downloaded to shared memory in 41.304s
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpwhi7uvff, device:0
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
rinen0721-mistral-dpo-0213-m3-v2-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.
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: quantized model in 38.236s
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: Processed model rinen0721/Mistral-dpo-0213-m3 in 79.541s
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: creating bucket guanaco-mkml-models
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rinen0721-mistral-dpo-0213-m3-v2
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rinen0721-mistral-dpo-0213-m3-v2/config.json
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rinen0721-mistral-dpo-0213-m3-v2/special_tokens_map.json
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rinen0721-mistral-dpo-0213-m3-v2/tokenizer_config.json
rinen0721-mistral-dpo-0213-m3-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rinen0721-mistral-dpo-0213-m3-v2/tokenizer.json
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Job rinen0721-mistral-dpo-0213-m3-v2-mkmlizer completed after 216.51s with status: succeeded
Stopping job with name rinen0721-mistral-dpo-0213-m3-v2-mkmlizer
Pipeline stage MKMLizer completed in 217.00s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.17s
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Running pipeline stage MKMLDeployer
Creating inference service rinen0721-mistral-dpo-0213-m3-v2
Waiting for inference service rinen0721-mistral-dpo-0213-m3-v2 to be ready
Inference service rinen0721-mistral-dpo-0213-m3-v2 ready after 200.7625274658203s
Pipeline stage MKMLDeployer completed in 201.26s
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Running pipeline stage StressChecker
Received healthy response to inference request in 1.5406713485717773s
Received healthy response to inference request in 1.8660492897033691s
Received healthy response to inference request in 1.165642499923706s
Received healthy response to inference request in 1.341501235961914s
Received healthy response to inference request in 1.4107599258422852s
5 requests
0 failed requests
5th percentile: 1.2008142471313477
10th percentile: 1.2359859943389893
20th percentile: 1.3063294887542725
30th percentile: 1.3553529739379884
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50th percentile: 1.4107599258422852
60th percentile: 1.462724494934082
70th percentile: 1.514689064025879
80th percentile: 1.6057469367980957
90th percentile: 1.7358981132507325
95th percentile: 1.8009737014770508
99th percentile: 1.8530341720581054
mean time: 1.4649248600006104
Pipeline stage StressChecker completed in 8.83s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 0.61s
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Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 2502.26s
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rinen0721-mistral-dpo-0213-m3_v2 status is now inactive due to auto deactivation removed underperforming models
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rinen0721-mistral-dpo-0213-m3_v2 status is now torndown due to DeploymentManager action