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Running pipeline stage MKMLizer
Starting job with name teknium-airoboros-mistr-79536-v1-mkmlizer
Waiting for job on teknium-airoboros-mistr-79536-v1-mkmlizer to finish
teknium-airoboros-mistr-79536-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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teknium-airoboros-mistr-79536-v1-mkmlizer: ║ ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ Version: 0.12.8 ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ https://mk1.ai ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ ║
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teknium-airoboros-mistr-79536-v1-mkmlizer: ║ belonging to: ║
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teknium-airoboros-mistr-79536-v1-mkmlizer: ║ Chai Research Corp. ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ Expiration: 2025-04-15 23:59:59 ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ║ ║
teknium-airoboros-mistr-79536-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
teknium-airoboros-mistr-79536-v1-mkmlizer: Downloaded to shared memory in 26.106s
teknium-airoboros-mistr-79536-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpf5ihlud8, device:0
teknium-airoboros-mistr-79536-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
teknium-airoboros-mistr-79536-v1-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.
teknium-airoboros-mistr-79536-v1-mkmlizer: tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
teknium-airoboros-mistr-79536-v1-mkmlizer: quantized model in 19.738s
teknium-airoboros-mistr-79536-v1-mkmlizer: Processed model teknium/airoboros-mistral2.2-7b in 45.845s
teknium-airoboros-mistr-79536-v1-mkmlizer: creating bucket guanaco-mkml-models
teknium-airoboros-mistr-79536-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
teknium-airoboros-mistr-79536-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1
teknium-airoboros-mistr-79536-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1/config.json
teknium-airoboros-mistr-79536-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1/tokenizer_config.json
teknium-airoboros-mistr-79536-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1/special_tokens_map.json
teknium-airoboros-mistr-79536-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1/tokenizer.model
teknium-airoboros-mistr-79536-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1/tokenizer.json
teknium-airoboros-mistr-79536-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/teknium-airoboros-mistr-79536-v1/flywheel_model.0.safetensors
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Job teknium-airoboros-mistr-79536-v1-mkmlizer completed after 73.7s with status: succeeded
Stopping job with name teknium-airoboros-mistr-79536-v1-mkmlizer
Pipeline stage MKMLizer completed in 74.18s
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Creating inference service teknium-airoboros-mistr-79536-v1
Waiting for inference service teknium-airoboros-mistr-79536-v1 to be ready
Inference service teknium-airoboros-mistr-79536-v1 ready after 220.72392630577087s
Pipeline stage MKMLDeployer completed in 221.25s
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Received healthy response to inference request in 2.1034460067749023s
Received healthy response to inference request in 1.3161427974700928s
Received healthy response to inference request in 1.218186378479004s
Received healthy response to inference request in 1.2666621208190918s
Received healthy response to inference request in 1.061492919921875s
5 requests
0 failed requests
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