developer_uid: WesPro
submission_id: wespro-miss-kunodolph_v3
model_name: wespro-miss-kunodolph_v3
model_group: WesPro/Miss_KunoDolph
status: torndown
timestamp: 2024-04-13T19:31:53+00:00
num_battles: 48766
num_wins: 19032
celo_rating: 1071.82
family_friendly_score: 0.0
submission_type: basic
model_repo: WesPro/Miss_KunoDolph
model_architecture: MistralForCausalLM
model_num_parameters: 7241732096.0
best_of: 4
max_input_tokens: 512
max_output_tokens: 64
reward_model: default
display_name: wespro-miss-kunodolph_v3
is_internal_developer: False
language_model: WesPro/Miss_KunoDolph
model_size: 7B
ranking_group: single
us_pacific_date: 2024-04-13
win_ratio: 0.39027191075749496
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, '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}:', 'truncate_by_message': False}
model_eval_status: success
reward_formatter: {'bot_template': '{bot_name}: {message}\n', 'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'response_template': '{bot_name}:', 'truncate_by_message': False, 'user_template': '{user_name}: {message}\n'}
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
Resubmit model
Running pipeline stage MKMLizer
Starting job with name wespro-miss-kunodolph-v3-mkmlizer
Waiting for job on wespro-miss-kunodolph-v3-mkmlizer to finish
wespro-miss-kunodolph-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
wespro-miss-kunodolph-v3-mkmlizer: ║ _____ __ __ ║
wespro-miss-kunodolph-v3-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
wespro-miss-kunodolph-v3-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
wespro-miss-kunodolph-v3-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
wespro-miss-kunodolph-v3-mkmlizer: ║ /___/ ║
wespro-miss-kunodolph-v3-mkmlizer: ║ ║
wespro-miss-kunodolph-v3-mkmlizer: ║ Version: 0.6.11 ║
wespro-miss-kunodolph-v3-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
wespro-miss-kunodolph-v3-mkmlizer: ║ ║
wespro-miss-kunodolph-v3-mkmlizer: ║ The license key for the current software has been verified as ║
wespro-miss-kunodolph-v3-mkmlizer: ║ belonging to: ║
wespro-miss-kunodolph-v3-mkmlizer: ║ ║
wespro-miss-kunodolph-v3-mkmlizer: ║ Chai Research Corp. ║
wespro-miss-kunodolph-v3-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
wespro-miss-kunodolph-v3-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
wespro-miss-kunodolph-v3-mkmlizer: ║ ║
wespro-miss-kunodolph-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
wespro-miss-kunodolph-v3-mkmlizer: mergekit_config.yml: 0%| | 0.00/438 [00:00<?, ?B/s] mergekit_config.yml: 100%|██████████| 438/438 [00:00<00:00, 3.98MB/s]
wespro-miss-kunodolph-v3-mkmlizer: model-00001-of-00002.safetensors: 0%| | 0.00/9.94G [00:00<?, ?B/s] model-00001-of-00002.safetensors: 0%| | 10.5M/9.94G [00:00<13:32, 12.2MB/s] model-00001-of-00002.safetensors: 0%| | 21.0M/9.94G [00:01<06:54, 23.9MB/s] model-00001-of-00002.safetensors: 0%| | 31.5M/9.94G [00:01<04:45, 34.7MB/s] model-00001-of-00002.safetensors: 0%| | 41.9M/9.94G [00:01<05:02, 32.7MB/s] model-00001-of-00002.safetensors: 1%| | 73.4M/9.94G [00:01<02:14, 73.4MB/s] model-00001-of-00002.safetensors: 1%| | 115M/9.94G [00:01<01:14, 132MB/s] model-00001-of-00002.safetensors: 2%|▏ | 178M/9.94G [00:01<00:42, 229MB/s] model-00001-of-00002.safetensors: 3%|▎ | 273M/9.94G [00:01<00:26, 368MB/s] model-00001-of-00002.safetensors: 8%|▊ | 765M/9.94G [00:02<00:06, 1.42GB/s] model-00001-of-00002.safetensors: 11%|█ | 1.11G/9.94G [00:02<00:04, 1.83GB/s] model-00001-of-00002.safetensors: 13%|█▎ | 1.33G/9.94G [00:02<00:08, 1.03GB/s] model-00001-of-00002.safetensors: 15%|█▌ | 1.50G/9.94G [00:02<00:08, 949MB/s] model-00001-of-00002.safetensors: 17%|█▋ | 1.65G/9.94G [00:02<00:08, 1.01GB/s] model-00001-of-00002.safetensors: 21%|██ | 2.11G/9.94G [00:03<00:04, 1.67GB/s] model-00001-of-00002.safetensors: 24%|██▎ | 2.35G/9.94G [00:03<00:05, 1.31GB/s] model-00001-of-00002.safetensors: 26%|██▌ | 2.54G/9.94G [00:03<00:05, 1.34GB/s] model-00001-of-00002.safetensors: 27%|██▋ | 2.72G/9.94G [00:03<00:05, 1.35GB/s] model-00001-of-00002.safetensors: 30%|██▉ | 2.98G/9.94G [00:03<00:04, 1.61GB/s] model-00001-of-00002.safetensors: 32%|███▏ | 3.18G/9.94G [00:03<00:05, 1.35GB/s] model-00001-of-00002.safetensors: 34%|███▎ | 3.34G/9.94G [00:04<00:05, 1.30GB/s] model-00001-of-00002.safetensors: 36%|███▌ | 3.59G/9.94G [00:04<00:04, 1.52GB/s] model-00001-of-00002.safetensors: 38%|███▊ | 3.83G/9.94G [00:04<00:03, 1.70GB/s] model-00001-of-00002.safetensors: 40%|████ | 4.03G/9.94G [00:04<00:04, 1.33GB/s] model-00001-of-00002.safetensors: 42%|████▏ | 4.19G/9.94G [00:04<00:04, 1.37GB/s] model-00001-of-00002.safetensors: 44%|████▍ | 4.39G/9.94G [00:04<00:03, 1.50GB/s] model-00001-of-00002.safetensors: 46%|████▋ | 4.61G/9.94G [00:04<00:03, 1.66GB/s] model-00001-of-00002.safetensors: 48%|████▊ | 4.80G/9.94G [00:04<00:03, 1.53GB/s] model-00001-of-00002.safetensors: 50%|████▉ | 4.97G/9.94G [00:05<00:04, 1.01GB/s] model-00001-of-00002.safetensors: 51%|█████▏ | 5.11G/9.94G [00:05<00:04, 1.01GB/s] model-00001-of-00002.safetensors: 53%|█████▎ | 5.28G/9.94G [00:05<00:03, 1.16GB/s] model-00001-of-00002.safetensors: 55%|█████▍ | 5.44G/9.94G [00:05<00:03, 1.25GB/s] model-00001-of-00002.safetensors: 56%|█████▌ | 5.59G/9.94G [00:05<00:03, 1.27GB/s] model-00001-of-00002.safetensors: 58%|█████▊ | 5.78G/9.94G [00:05<00:03, 1.34GB/s] model-00001-of-00002.safetensors: 60%|█████▉ | 5.92G/9.94G [00:05<00:03, 1.32GB/s] model-00001-of-00002.safetensors: 61%|██████▏ | 6.10G/9.94G [00:06<00:02, 1.43GB/s] model-00001-of-00002.safetensors: 63%|██████▎ | 6.30G/9.94G [00:06<00:02, 1.58GB/s] model-00001-of-00002.safetensors: 65%|██████▌ | 6.47G/9.94G [00:06<00:02, 1.53GB/s] model-00001-of-00002.safetensors: 67%|██████▋ | 6.64G/9.94G [00:06<00:02, 1.52GB/s] model-00001-of-00002.safetensors: 69%|██████▊ | 6.83G/9.94G [00:06<00:01, 1.61GB/s] model-00001-of-00002.safetensors: 70%|███████ | 6.99G/9.94G [00:06<00:02, 1.38GB/s] model-00001-of-00002.safetensors: 72%|███████▏ | 7.20G/9.94G [00:06<00:01, 1.55GB/s] model-00001-of-00002.safetensors: 74%|███████▍ | 7.37G/9.94G [00:06<00:01, 1.45GB/s] model-00001-of-00002.safetensors: 76%|███████▋ | 7.60G/9.94G [00:07<00:01, 1.64GB/s] model-00001-of-00002.safetensors: 78%|███████▊ | 7.78G/9.94G [00:07<00:01, 1.60GB/s] model-00001-of-00002.safetensors: 80%|███████▉ | 7.95G/9.94G [00:07<00:01, 1.23GB/s] model-00001-of-00002.safetensors: 81%|████████▏ | 8.10G/9.94G [00:07<00:01, 1.27GB/s] model-00001-of-00002.safetensors: 83%|████████▎ | 8.25G/9.94G [00:07<00:01, 1.33GB/s] model-00001-of-00002.safetensors: 85%|████████▌ | 8.46G/9.94G [00:07<00:00, 1.52GB/s] model-00001-of-00002.safetensors: 87%|████████▋ | 8.63G/9.94G [00:07<00:00, 1.43GB/s] model-00001-of-00002.safetensors: 89%|████████▊ | 8.82G/9.94G [00:07<00:00, 1.54GB/s] model-00001-of-00002.safetensors: 90%|█████████ | 8.99G/9.94G [00:07<00:00, 1.56GB/s] model-00001-of-00002.safetensors: 92%|█████████▏| 9.15G/9.94G [00:08<00:00, 1.33GB/s] model-00001-of-00002.safetensors: 96%|█████████▌| 9.54G/9.94G [00:08<00:00, 1.96GB/s] model-00001-of-00002.safetensors: 100%|█████████▉| 9.94G/9.94G [00:08<00:00, 1.19GB/s]
wespro-miss-kunodolph-v3-mkmlizer: model-00002-of-00002.safetensors: 0%| | 0.00/4.54G [00:00<?, ?B/s] model-00002-of-00002.safetensors: 0%| | 10.5M/4.54G [00:00<06:31, 11.6MB/s] model-00002-of-00002.safetensors: 0%| | 21.0M/4.54G [00:01<04:05, 18.4MB/s] model-00002-of-00002.safetensors: 1%| | 52.4M/4.54G [00:01<01:41, 44.4MB/s] model-00002-of-00002.safetensors: 2%|▏ | 73.4M/4.54G [00:01<01:10, 63.1MB/s] model-00002-of-00002.safetensors: 4%|▍ | 178M/4.54G [00:01<00:21, 200MB/s] model-00002-of-00002.safetensors: 18%|█▊ | 797M/4.54G [00:01<00:03, 1.21GB/s] model-00002-of-00002.safetensors: 24%|██▍ | 1.10G/4.54G [00:02<00:02, 1.45GB/s] model-00002-of-00002.safetensors: 29%|██▉ | 1.33G/4.54G [00:02<00:02, 1.16GB/s] model-00002-of-00002.safetensors: 33%|███▎ | 1.52G/4.54G [00:02<00:02, 1.06GB/s] model-00002-of-00002.safetensors: 42%|████▏ | 1.92G/4.54G [00:02<00:01, 1.54GB/s] model-00002-of-00002.safetensors: 48%|████▊ | 2.18G/4.54G [00:02<00:01, 1.71GB/s] model-00002-of-00002.safetensors: 53%|█████▎ | 2.41G/4.54G [00:03<00:01, 1.45GB/s] model-00002-of-00002.safetensors: 57%|█████▋ | 2.60G/4.54G [00:03<00:01, 1.37GB/s] model-00002-of-00002.safetensors: 63%|██████▎ | 2.85G/4.54G [00:03<00:01, 1.59GB/s] model-00002-of-00002.safetensors: 67%|██████▋ | 3.06G/4.54G [00:03<00:00, 1.69GB/s] model-00002-of-00002.safetensors: 72%|███████▏ | 3.26G/4.54G [00:03<00:00, 1.63GB/s] model-00002-of-00002.safetensors: 76%|███████▌ | 3.45G/4.54G [00:03<00:00, 1.48GB/s] model-00002-of-00002.safetensors: 80%|███████▉ | 3.62G/4.54G [00:03<00:00, 1.43GB/s] model-00002-of-00002.safetensors: 86%|████████▌ | 3.90G/4.54G [00:03<00:00, 1.76GB/s] model-00002-of-00002.safetensors: 95%|█████████▍| 4.30G/4.54G [00:04<00:00, 2.30GB/s] model-00002-of-00002.safetensors: 100%|█████████▉| 4.54G/4.54G [00:04<00:00, 1.10GB/s]
wespro-miss-kunodolph-v3-mkmlizer: model.safetensors.index.json: 0%| | 0.00/22.8k [00:00<?, ?B/s] model.safetensors.index.json: 100%|██████████| 22.8k/22.8k [00:00<00:00, 6.05MB/s]
wespro-miss-kunodolph-v3-mkmlizer: special_tokens_map.json: 0%| | 0.00/414 [00:00<?, ?B/s] special_tokens_map.json: 100%|██████████| 414/414 [00:00<00:00, 5.03MB/s]
wespro-miss-kunodolph-v3-mkmlizer: tokenizer.json: 0%| | 0.00/1.80M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 1.80M/1.80M [00:00<00:00, 7.17MB/s] tokenizer.json: 100%|██████████| 1.80M/1.80M [00:00<00:00, 7.15MB/s]
wespro-miss-kunodolph-v3-mkmlizer: tokenizer.model: 0%| | 0.00/493k [00:00<?, ?B/s] tokenizer.model: 100%|██████████| 493k/493k [00:00<00:00, 2.50MB/s] tokenizer.model: 100%|██████████| 493k/493k [00:00<00:00, 2.50MB/s]
wespro-miss-kunodolph-v3-mkmlizer: tokenizer_config.json: 0%| | 0.00/1.46k [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 1.46k/1.46k [00:00<00:00, 12.9MB/s]
wespro-miss-kunodolph-v3-mkmlizer: Downloaded to shared memory in 16.331s
wespro-miss-kunodolph-v3-mkmlizer: quantizing model to /dev/shm/model_cache
wespro-miss-kunodolph-v3-mkmlizer: Saving mkml model at /dev/shm/model_cache
wespro-miss-kunodolph-v3-mkmlizer: Reading /tmp/tmpbynazhp9/model.safetensors.index.json
wespro-miss-kunodolph-v3-mkmlizer: quantized model in 17.617s
wespro-miss-kunodolph-v3-mkmlizer: Processed model WesPro/Miss_KunoDolph in 35.003s
wespro-miss-kunodolph-v3-mkmlizer: creating bucket guanaco-mkml-models
wespro-miss-kunodolph-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
wespro-miss-kunodolph-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/wespro-miss-kunodolph-v3
wespro-miss-kunodolph-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/wespro-miss-kunodolph-v3/config.json
wespro-miss-kunodolph-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/wespro-miss-kunodolph-v3/special_tokens_map.json
wespro-miss-kunodolph-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/wespro-miss-kunodolph-v3/tokenizer_config.json
wespro-miss-kunodolph-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/wespro-miss-kunodolph-v3/tokenizer.model
wespro-miss-kunodolph-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/wespro-miss-kunodolph-v3/tokenizer.json
wespro-miss-kunodolph-v3-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/wespro-miss-kunodolph-v3/mkml_model.tensors
wespro-miss-kunodolph-v3-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
wespro-miss-kunodolph-v3-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.
wespro-miss-kunodolph-v3-mkmlizer: warnings.warn(
wespro-miss-kunodolph-v3-mkmlizer: config.json: 0%| | 0.00/1.05k [00:00<?, ?B/s] config.json: 100%|██████████| 1.05k/1.05k [00:00<00:00, 13.1MB/s]
wespro-miss-kunodolph-v3-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.
wespro-miss-kunodolph-v3-mkmlizer: warnings.warn(
wespro-miss-kunodolph-v3-mkmlizer: tokenizer_config.json: 0%| | 0.00/234 [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 234/234 [00:00<00:00, 1.70MB/s]
wespro-miss-kunodolph-v3-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 4.45MB/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 4.44MB/s]
wespro-miss-kunodolph-v3-mkmlizer: tokenizer.json: 0%| | 0.00/2.11M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 2.11M/2.11M [00:00<00:00, 25.4MB/s]
wespro-miss-kunodolph-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:472: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
wespro-miss-kunodolph-v3-mkmlizer: warnings.warn(
wespro-miss-kunodolph-v3-mkmlizer: pytorch_model.bin: 0%| | 0.00/1.44G [00:00<?, ?B/s] pytorch_model.bin: 1%| | 10.5M/1.44G [00:00<01:56, 12.3MB/s] pytorch_model.bin: 1%|▏ | 21.0M/1.44G [00:00<00:56, 25.0MB/s] pytorch_model.bin: 3%|▎ | 41.9M/1.44G [00:01<00:48, 29.0MB/s] pytorch_model.bin: 4%|▎ | 52.4M/1.44G [00:01<00:40, 34.4MB/s] pytorch_model.bin: 7%|▋ | 94.4M/1.44G [00:01<00:16, 80.4MB/s] pytorch_model.bin: 17%|█▋ | 252M/1.44G [00:02<00:03, 302MB/s] pytorch_model.bin: 53%|█████▎ | 765M/1.44G [00:02<00:00, 1.15GB/s] pytorch_model.bin: 75%|███████▌ | 1.09G/1.44G [00:02<00:00, 1.55GB/s] pytorch_model.bin: 93%|█████████▎| 1.34G/1.44G [00:02<00:00, 1.70GB/s] pytorch_model.bin: 100%|█████████▉| 1.44G/1.44G [00:02<00:00, 610MB/s]
wespro-miss-kunodolph-v3-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
wespro-miss-kunodolph-v3-mkmlizer: Saving duration: 0.306s
wespro-miss-kunodolph-v3-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 7.389s
wespro-miss-kunodolph-v3-mkmlizer: creating bucket guanaco-reward-models
wespro-miss-kunodolph-v3-mkmlizer: Bucket 's3://guanaco-reward-models/' created
wespro-miss-kunodolph-v3-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/config.json
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/special_tokens_map.json
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/tokenizer_config.json
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/merges.txt
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/vocab.json
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/tokenizer.json
wespro-miss-kunodolph-v3-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/wespro-miss-kunodolph-v3_reward/reward.tensors
Job wespro-miss-kunodolph-v3-mkmlizer completed after 74.42s with status: succeeded
Stopping job with name wespro-miss-kunodolph-v3-mkmlizer
Pipeline stage MKMLizer completed in 75.38s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service wespro-miss-kunodolph-v3
Waiting for inference service wespro-miss-kunodolph-v3 to be ready
Inference service wespro-miss-kunodolph-v3 ready after 50.2748761177063s
Pipeline stage ISVCDeployer completed in 56.24s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.5009121894836426s
Received healthy response to inference request in 0.9825448989868164s
Received healthy response to inference request in 1.0593008995056152s
Received healthy response to inference request in 1.0324645042419434s
Received healthy response to inference request in 1.0755531787872314s
5 requests
0 failed requests
5th percentile: 0.9925288200378418
10th percentile: 1.0025127410888672
20th percentile: 1.022480583190918
30th percentile: 1.0378317832946777
40th percentile: 1.0485663414001465
50th percentile: 1.0593008995056152
60th percentile: 1.0658018112182617
70th percentile: 1.0723027229309081
80th percentile: 1.1606249809265137
90th percentile: 1.3307685852050781
95th percentile: 1.4158403873443604
99th percentile: 1.483897829055786
mean time: 1.1301551342010498
Pipeline stage StressChecker completed in 6.44s
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 0.04s
M-Eval Dataset for topic stay_in_character is loaded
wespro-miss-kunodolph_v3 status is now deployed due to DeploymentManager action
wespro-miss-kunodolph_v3 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of wespro-miss-kunodolph_v3
Running pipeline stage ISVCDeleter
Checking if service wespro-miss-kunodolph-v3 is running
Tearing down inference service wespro-miss-kunodolph-v3
Toredown service wespro-miss-kunodolph-v3
Pipeline stage ISVCDeleter completed in 7.72s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key wespro-miss-kunodolph-v3/config.json from bucket guanaco-mkml-models
Deleting key wespro-miss-kunodolph-v3/mkml_model.tensors from bucket guanaco-mkml-models
Deleting key wespro-miss-kunodolph-v3/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key wespro-miss-kunodolph-v3/tokenizer.json from bucket guanaco-mkml-models
Deleting key wespro-miss-kunodolph-v3/tokenizer.model from bucket guanaco-mkml-models
Deleting key wespro-miss-kunodolph-v3/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key wespro-miss-kunodolph-v3_reward/config.json from bucket guanaco-reward-models
Deleting key wespro-miss-kunodolph-v3_reward/merges.txt from bucket guanaco-reward-models
Deleting key wespro-miss-kunodolph-v3_reward/reward.tensors from bucket guanaco-reward-models
Deleting key wespro-miss-kunodolph-v3_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key wespro-miss-kunodolph-v3_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key wespro-miss-kunodolph-v3_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key wespro-miss-kunodolph-v3_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 1.92s
wespro-miss-kunodolph_v3 status is now torndown due to DeploymentManager action