Running pipeline stage MKMLizer
Starting job with name cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer
Waiting for job on cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer to finish
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ║ ║
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ║ Version: 0.8.14 ║
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ║ https://mk1.ai ║
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cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ║ Chai Research Corp. ║
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cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:131: FutureWarning: 'list_files_info' (from 'huggingface_hub.hf_api') is deprecated and will be removed from version '0.23'. Use `list_repo_tree` and `get_paths_info` instead.
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Downloaded to shared memory in 37.415s
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: quantizing model to /dev/shm/model_cache
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer:
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: quantized model in 24.068s
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Processed model cgato/L3-TheSpice-8b-DPO-v3.2-e15.1 in 64.166s
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: creating bucket guanaco-mkml-models
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cgato-l3-thespice-8b-dpo-1421-v1
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cgato-l3-thespice-8b-dpo-1421-v1/config.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cgato-l3-thespice-8b-dpo-1421-v1/special_tokens_map.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cgato-l3-thespice-8b-dpo-1421-v1/tokenizer_config.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cgato-l3-thespice-8b-dpo-1421-v1/tokenizer.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cgato-l3-thespice-8b-dpo-1421-v1/flywheel_model.0.safetensors
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:913: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: warnings.warn(
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:757: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: warnings.warn(
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:468: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: warnings.warn(
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: return self.fget.__get__(instance, owner)()
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Saving duration: 0.428s
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 4.251s
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: creating bucket guanaco-reward-models
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/special_tokens_map.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/config.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/merges.txt
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/tokenizer_config.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/vocab.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/tokenizer.json
cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/cgato-l3-thespice-8b-dpo-1421-v1_reward/reward.tensors
Job cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer completed after 83.58s with status: succeeded
Stopping job with name cgato-l3-thespice-8b-dpo-1421-v1-mkmlizer
Pipeline stage MKMLizer completed in 83.90s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service cgato-l3-thespice-8b-dpo-1421-v1
Waiting for inference service cgato-l3-thespice-8b-dpo-1421-v1 to be ready
Inference service cgato-l3-thespice-8b-dpo-1421-v1 ready after 40.37156295776367s
Pipeline stage ISVCDeployer completed in 45.92s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.2128825187683105s
Received healthy response to inference request in 1.3329553604125977s
Received healthy response to inference request in 1.3149843215942383s
Received healthy response to inference request in 1.318934679031372s
Received healthy response to inference request in 1.2870595455169678s
5 requests
0 failed requests
5th percentile: 1.2926445007324219
10th percentile: 1.298229455947876
20th percentile: 1.3093993663787842
30th percentile: 1.315774393081665
40th percentile: 1.3173545360565186
50th percentile: 1.318934679031372
60th percentile: 1.3245429515838623
70th percentile: 1.3301512241363525
80th percentile: 1.5089407920837403
90th percentile: 1.8609116554260254
95th percentile: 2.036897087097168
99th percentile: 2.177685432434082
mean time: 1.4933632850646972
Pipeline stage StressChecker completed in 8.03s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.03s
Running pipeline stage DaemonicSafetyScorer
Running M-Eval for topic stay_in_character
Pipeline stage DaemonicSafetyScorer completed in 0.04s
M-Eval Dataset for topic stay_in_character is loaded
cgato-l3-thespice-8b-dpo_1421_v1 status is now deployed due to DeploymentManager action
cgato-l3-thespice-8b-dpo_1421_v1 status is now rejected due to its M-Eval score being less than the acceptable minimum 6.5 to serve to users. Please consider iterating on your model's ability to adhere to prompts to improve this score.