submission_id: nitral-ai-kukulstanta-7b_v1
developer_uid: Nitral-AI
status: inactive
model_repo: Nitral-AI/KukulStanta-7B
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 4, 'max_output_tokens': 64}
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}:'}
reward_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}:'}
timestamp: 2024-03-31T19:38:52+00:00
model_name: nitral-ai-kukulstanta-7b_v1
model_eval_status: success
safety_score: 0.98
entertaining: 7.04
stay_in_character: 8.73
user_preference: 7.66
double_thumbs_up: 116
thumbs_up: 207
thumbs_down: 67
num_battles: 12113
num_wins: 6133
win_ratio: 0.5063155287707422
celo_rating: 1161.84
Resubmit model
Running pipeline stage MKMLizer
Starting job with name nitral-ai-kukulstanta-7b-v1-mkmlizer
Waiting for job on nitral-ai-kukulstanta-7b-v1-mkmlizer to finish
nitral-ai-kukulstanta-7b-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ _____ __ __ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ /___/ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ Version: 0.6.11 ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ The license key for the current software has been verified as ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ belonging to: ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ Chai Research Corp. ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ║ ║
nitral-ai-kukulstanta-7b-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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nitral-ai-kukulstanta-7b-v1-mkmlizer: Downloaded to shared memory in 34.399s
nitral-ai-kukulstanta-7b-v1-mkmlizer: quantizing model to /dev/shm/model_cache
nitral-ai-kukulstanta-7b-v1-mkmlizer: Saving mkml model at /dev/shm/model_cache
nitral-ai-kukulstanta-7b-v1-mkmlizer: Reading /tmp/tmpc_nzfpse/model.safetensors.index.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:00<00:40, 7.22it/s] Profiling: 3%|▎ | 10/291 [00:00<00:05, 47.10it/s] Profiling: 7%|▋ | 20/291 [00:00<00:04, 67.42it/s] Profiling: 10%|█ | 30/291 [00:00<00:03, 77.44it/s] Profiling: 13%|█▎ | 39/291 [00:00<00:04, 57.69it/s] Profiling: 17%|█▋ | 49/291 [00:00<00:03, 67.23it/s] Profiling: 21%|██▏ | 62/291 [00:00<00:02, 83.57it/s] Profiling: 25%|██▌ | 74/291 [00:01<00:02, 90.06it/s] Profiling: 29%|██▉ | 84/291 [00:01<00:02, 71.26it/s] Profiling: 32%|███▏ | 94/291 [00:01<00:02, 76.75it/s] Profiling: 36%|███▌ | 104/291 [00:01<00:02, 81.82it/s] Profiling: 40%|████ | 117/291 [00:01<00:01, 93.92it/s] Profiling: 44%|████▍ | 128/291 [00:01<00:02, 71.21it/s] Profiling: 47%|████▋ | 138/291 [00:01<00:01, 76.98it/s] Profiling: 53%|█████▎ | 153/291 [00:01<00:01, 90.26it/s] Profiling: 56%|█████▌ | 163/291 [00:03<00:06, 18.63it/s] Profiling: 59%|█████▉ | 173/291 [00:03<00:04, 23.91it/s] Profiling: 64%|██████▍ | 187/291 [00:03<00:03, 33.80it/s] Profiling: 68%|██████▊ | 197/291 [00:05<00:05, 16.62it/s] Profiling: 71%|███████ | 206/291 [00:05<00:04, 20.95it/s] Profiling: 75%|███████▍ | 217/291 [00:05<00:02, 27.51it/s] Profiling: 79%|███████▉ | 231/291 [00:05<00:01, 35.89it/s] Profiling: 83%|████████▎ | 241/291 [00:05<00:01, 42.96it/s] Profiling: 86%|████████▋ | 251/291 [00:05<00:00, 50.63it/s] Profiling: 90%|████████▉ | 261/291 [00:06<00:00, 58.50it/s] Profiling: 94%|█████████▍| 274/291 [00:06<00:00, 59.25it/s] Profiling: 98%|█████████▊| 284/291 [00:06<00:00, 65.72it/s] Profiling: 100%|██████████| 291/291 [00:06<00:00, 44.59it/s]
nitral-ai-kukulstanta-7b-v1-mkmlizer: quantized model in 17.193s
nitral-ai-kukulstanta-7b-v1-mkmlizer: Processed model Nitral-AI/KukulStanta-7B in 52.891s
nitral-ai-kukulstanta-7b-v1-mkmlizer: creating bucket guanaco-mkml-models
nitral-ai-kukulstanta-7b-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
nitral-ai-kukulstanta-7b-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1/special_tokens_map.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1/config.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1/tokenizer.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1/tokenizer_config.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1/tokenizer.model
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/nitral-ai-kukulstanta-7b-v1/mkml_model.tensors
nitral-ai-kukulstanta-7b-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
nitral-ai-kukulstanta-7b-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:1067: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
nitral-ai-kukulstanta-7b-v1-mkmlizer: warnings.warn(
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nitral-ai-kukulstanta-7b-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:690: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
nitral-ai-kukulstanta-7b-v1-mkmlizer: warnings.warn(
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nitral-ai-kukulstanta-7b-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
nitral-ai-kukulstanta-7b-v1-mkmlizer: Saving duration: 0.272s
nitral-ai-kukulstanta-7b-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 6.215s
nitral-ai-kukulstanta-7b-v1-mkmlizer: creating bucket guanaco-reward-models
nitral-ai-kukulstanta-7b-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
nitral-ai-kukulstanta-7b-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/config.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/special_tokens_map.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/tokenizer_config.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/vocab.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/merges.txt
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/tokenizer.json
nitral-ai-kukulstanta-7b-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/nitral-ai-kukulstanta-7b-v1_reward/reward.tensors
Job nitral-ai-kukulstanta-7b-v1-mkmlizer completed after 84.78s with status: succeeded
Stopping job with name nitral-ai-kukulstanta-7b-v1-mkmlizer
Pipeline stage MKMLizer completed in 89.88s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service nitral-ai-kukulstanta-7b-v1
Waiting for inference service nitral-ai-kukulstanta-7b-v1 to be ready
Inference service nitral-ai-kukulstanta-7b-v1 ready after 40.355586528778076s
Pipeline stage ISVCDeployer completed in 47.82s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.5820887088775635s
Received healthy response to inference request in 1.0791842937469482s
Received healthy response to inference request in 0.9245595932006836s
Received healthy response to inference request in 1.0777308940887451s
Received healthy response to inference request in 1.0768311023712158s
5 requests
0 failed requests
5th percentile: 0.9550138950347901
10th percentile: 0.9854681968688965
20th percentile: 1.0463768005371095
30th percentile: 1.0770110607147216
40th percentile: 1.0773709774017335
50th percentile: 1.0777308940887451
60th percentile: 1.0783122539520265
70th percentile: 1.0788936138153076
80th percentile: 1.1797651767730715
90th percentile: 1.3809269428253175
95th percentile: 1.4815078258514403
99th percentile: 1.5619725322723388
mean time: 1.1480789184570312
Pipeline stage StressChecker completed in 6.54s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.04s
Running pipeline stage DaemonicSafetyScorer
Running M-Eval for topic stay_in_character
Pipeline stage DaemonicSafetyScorer completed in 0.05s
M-Eval Dataset for topic stay_in_character is loaded
nitral-ai-kukulstanta-7b_v1 status is now deployed due to DeploymentManager action
nitral-ai-kukulstanta-7b_v1 status is now inactive due to auto deactivation removed underperforming models

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