submission_id: deverdever-heavenly-goat-v5_v2
developer_uid: clover0103
best_of: 16
celo_rating: 1159.66
display_name: heavenly-goat-v5
family_friendly_score: 0.0
formatter: {'memory_template': "### Instruction:\nYou are a creative agent roleplaying as a character called {bot_name}. Stay true to the persona given, reply with short and descriptive sentences. Do not be repetitive.\n{bot_name}'s Persona: {memory}\n", 'prompt_template': '### Input:\n# Example conversation:\n{prompt}\n# Actual conversation:\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': 'User: {message}\n', 'response_template': '### Response:\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 0.8, 'top_p': 0.9, 'min_p': 0.0, 'top_k': 30, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
is_internal_developer: False
language_model: DeverDever/heavenly-goat-v5
max_input_tokens: 512
max_output_tokens: 64
model_eval_status: success
model_group: DeverDever/heavenly-goat
model_name: heavenly-goat-v5
model_num_parameters: 7241732096.0
model_repo: DeverDever/heavenly-goat-v5
model_size: 7B
num_battles: 67293
num_wins: 33886
ranking_group: single
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
status: torndown
submission_type: basic
timestamp: 2024-03-18T02:32:30+00:00
us_pacific_date: 2024-03-17
win_ratio: 0.503559062606809
Resubmit model
Running pipeline stage MKMLizer
Starting job with name deverdever-heavenly-goat-v5-v2-mkmlizer
Waiting for job on deverdever-heavenly-goat-v5-v2-mkmlizer to finish
deverdever-heavenly-goat-v5-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ _____ __ __ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ /___/ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ Version: 0.6.11 ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ The license key for the current software has been verified as ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ belonging to: ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ Chai Research Corp. ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ Expiration: 2024-04-15 23:59:59 ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ║ ║
deverdever-heavenly-goat-v5-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
deverdever-heavenly-goat-v5-v2-mkmlizer: .gitattributes: 0%| | 0.00/1.52k [00:00<?, ?B/s] .gitattributes: 100%|██████████| 1.52k/1.52k [00:00<00:00, 18.5MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: README.md: 0%| | 0.00/21.0 [00:00<?, ?B/s] README.md: 100%|██████████| 21.0/21.0 [00:00<00:00, 287kB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: config.json: 0%| | 0.00/639 [00:00<?, ?B/s] config.json: 100%|██████████| 639/639 [00:00<00:00, 8.54MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: generation_config.json: 0%| | 0.00/137 [00:00<?, ?B/s] generation_config.json: 100%|██████████| 137/137 [00:00<00:00, 1.84MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: pytorch_model-00001-of-00003.bin: 0%| | 0.00/4.94G [00:00<?, ?B/s] pytorch_model-00001-of-00003.bin: 0%| | 10.5M/4.94G [00:01<10:59, 7.48MB/s] pytorch_model-00001-of-00003.bin: 1%|▏ | 62.9M/4.94G [00:01<01:30, 54.2MB/s] pytorch_model-00001-of-00003.bin: 3%|▎ | 168M/4.94G [00:01<00:30, 156MB/s] pytorch_model-00001-of-00003.bin: 4%|▍ | 220M/4.94G [00:01<00:25, 183MB/s] pytorch_model-00001-of-00003.bin: 6%|▌ | 283M/4.94G [00:01<00:19, 243MB/s] pytorch_model-00001-of-00003.bin: 7%|▋ | 336M/4.94G [00:02<00:16, 274MB/s] pytorch_model-00001-of-00003.bin: 8%|▊ | 388M/4.94G [00:02<00:14, 306MB/s] pytorch_model-00001-of-00003.bin: 9%|▉ | 461M/4.94G [00:02<00:13, 339MB/s] pytorch_model-00001-of-00003.bin: 10%|█ | 514M/4.94G [00:02<00:11, 370MB/s] pytorch_model-00001-of-00003.bin: 11%|█▏ | 566M/4.94G [00:02<00:11, 365MB/s] pytorch_model-00001-of-00003.bin: 12%|█▏ | 608M/4.94G [00:02<00:11, 369MB/s] pytorch_model-00001-of-00003.bin: 13%|█▎ | 650M/4.94G [00:02<00:12, 339MB/s] pytorch_model-00001-of-00003.bin: 14%|█▍ | 713M/4.94G [00:03<00:11, 383MB/s] pytorch_model-00001-of-00003.bin: 15%|█▌ | 765M/4.94G [00:03<00:11, 375MB/s] pytorch_model-00001-of-00003.bin: 16%|█▋ | 807M/4.94G [00:03<00:10, 385MB/s] pytorch_model-00001-of-00003.bin: 21%|██ | 1.03G/4.94G [00:03<00:04, 835MB/s] pytorch_model-00001-of-00003.bin: 23%|██▎ | 1.12G/4.94G [00:03<00:05, 703MB/s] pytorch_model-00001-of-00003.bin: 24%|██▍ | 1.21G/4.94G [00:03<00:05, 711MB/s] pytorch_model-00001-of-00003.bin: 34%|███▎ | 1.66G/4.94G [00:03<00:02, 1.63GB/s] pytorch_model-00001-of-00003.bin: 38%|███▊ | 1.90G/4.94G [00:03<00:01, 1.69GB/s] pytorch_model-00001-of-00003.bin: 42%|████▏ | 2.09G/4.94G [00:04<00:04, 596MB/s] pytorch_model-00001-of-00003.bin: 45%|████▌ | 2.23G/4.94G [00:04<00:03, 688MB/s] pytorch_model-00001-of-00003.bin: 48%|████▊ | 2.38G/4.94G [00:05<00:03, 649MB/s] pytorch_model-00001-of-00003.bin: 50%|█████ | 2.50G/4.94G [00:05<00:03, 658MB/s] pytorch_model-00001-of-00003.bin: 53%|█████▎ | 2.60G/4.94G [00:05<00:03, 703MB/s] pytorch_model-00001-of-00003.bin: 55%|█████▍ | 2.71G/4.94G [00:05<00:02, 753MB/s] pytorch_model-00001-of-00003.bin: 57%|█████▋ | 2.81G/4.94G [00:05<00:02, 796MB/s] pytorch_model-00001-of-00003.bin: 59%|█████▉ | 2.94G/4.94G [00:05<00:02, 888MB/s] pytorch_model-00001-of-00003.bin: 62%|██████▏ | 3.04G/4.94G [00:05<00:02, 827MB/s] pytorch_model-00001-of-00003.bin: 63%|██████▎ | 3.14G/4.94G [00:06<00:02, 822MB/s] pytorch_model-00001-of-00003.bin: 65%|██████▌ | 3.23G/4.94G [00:06<00:02, 841MB/s] pytorch_model-00001-of-00003.bin: 67%|██████▋ | 3.32G/4.94G [00:06<00:01, 866MB/s] pytorch_model-00001-of-00003.bin: 69%|██████▉ | 3.42G/4.94G [00:06<00:01, 801MB/s] pytorch_model-00001-of-00003.bin: 72%|███████▏ | 3.55G/4.94G [00:06<00:01, 942MB/s] pytorch_model-00001-of-00003.bin: 74%|███████▍ | 3.67G/4.94G [00:06<00:01, 971MB/s] pytorch_model-00001-of-00003.bin: 77%|███████▋ | 3.80G/4.94G [00:06<00:01, 1.02GB/s] pytorch_model-00001-of-00003.bin: 79%|███████▉ | 3.90G/4.94G [00:06<00:01, 961MB/s] pytorch_model-00001-of-00003.bin: 81%|████████ | 4.01G/4.94G [00:06<00:00, 983MB/s] pytorch_model-00001-of-00003.bin: 83%|████████▎ | 4.11G/4.94G [00:07<00:00, 894MB/s] pytorch_model-00001-of-00003.bin: 93%|█████████▎| 4.60G/4.94G [00:07<00:00, 1.92GB/s] pytorch_model-00001-of-00003.bin: 97%|█████████▋| 4.81G/4.94G [00:07<00:00, 1.21GB/s] pytorch_model-00001-of-00003.bin: 100%|█████████▉| 4.94G/4.94G [00:07<00:00, 637MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: pytorch_model-00002-of-00003.bin: 0%| | 0.00/5.00G [00:00<?, ?B/s] pytorch_model-00002-of-00003.bin: 0%| | 10.5M/5.00G [00:01<12:10, 6.83MB/s] pytorch_model-00002-of-00003.bin: 0%| | 21.0M/5.00G [00:01<06:04, 13.7MB/s] pytorch_model-00002-of-00003.bin: 1%| | 52.4M/5.00G [00:02<02:13, 37.0MB/s] pytorch_model-00002-of-00003.bin: 1%|▏ | 73.4M/5.00G [00:02<01:32, 53.0MB/s] pytorch_model-00002-of-00003.bin: 2%|▏ | 105M/5.00G [00:02<01:14, 65.5MB/s] pytorch_model-00002-of-00003.bin: 3%|▎ | 126M/5.00G [00:02<01:04, 76.1MB/s] pytorch_model-00002-of-00003.bin: 3%|▎ | 136M/5.00G [00:02<01:03, 76.1MB/s] pytorch_model-00002-of-00003.bin: 3%|▎ | 147M/5.00G [00:02<01:02, 77.8MB/s] pytorch_model-00002-of-00003.bin: 3%|▎ | 168M/5.00G [00:03<00:51, 93.3MB/s] pytorch_model-00002-of-00003.bin: 4%|▍ | 189M/5.00G [00:03<00:46, 104MB/s] pytorch_model-00002-of-00003.bin: 4%|▍ | 210M/5.00G [00:03<00:46, 103MB/s] pytorch_model-00002-of-00003.bin: 5%|▍ | 231M/5.00G [00:03<00:44, 108MB/s] pytorch_model-00002-of-00003.bin: 5%|▌ | 262M/5.00G [00:03<00:34, 137MB/s] pytorch_model-00002-of-00003.bin: 7%|▋ | 367M/5.00G [00:03<00:14, 318MB/s] pytorch_model-00002-of-00003.bin: 10%|▉ | 482M/5.00G [00:04<00:09, 492MB/s] pytorch_model-00002-of-00003.bin: 11%|█ | 545M/5.00G [00:04<00:09, 490MB/s] pytorch_model-00002-of-00003.bin: 13%|█▎ | 629M/5.00G [00:04<00:07, 572MB/s] pytorch_model-00002-of-00003.bin: 26%|██▌ | 1.31G/5.00G [00:04<00:02, 1.45GB/s] pytorch_model-00002-of-00003.bin: 29%|██▊ | 1.43G/5.00G [00:05<00:07, 479MB/s] pytorch_model-00002-of-00003.bin: 30%|███ | 1.51G/5.00G [00:05<00:07, 467MB/s] pytorch_model-00002-of-00003.bin: 32%|███▏ | 1.58G/5.00G [00:05<00:06, 490MB/s] pytorch_model-00002-of-00003.bin: 33%|███▎ | 1.66G/5.00G [00:06<00:06, 520MB/s] pytorch_model-00002-of-00003.bin: 35%|███▍ | 1.73G/5.00G [00:06<00:06, 497MB/s] pytorch_model-00002-of-00003.bin: 36%|███▌ | 1.79G/5.00G [00:06<00:06, 493MB/s] pytorch_model-00002-of-00003.bin: 37%|███▋ | 1.87G/5.00G [00:06<00:05, 532MB/s] pytorch_model-00002-of-00003.bin: 39%|███▊ | 1.93G/5.00G [00:06<00:05, 551MB/s] pytorch_model-00002-of-00003.bin: 41%|████ | 2.03G/5.00G [00:06<00:04, 661MB/s] pytorch_model-00002-of-00003.bin: 43%|████▎ | 2.13G/5.00G [00:06<00:04, 591MB/s] pytorch_model-00002-of-00003.bin: 44%|████▍ | 2.22G/5.00G [00:06<00:04, 651MB/s] pytorch_model-00002-of-00003.bin: 47%|████▋ | 2.36G/5.00G [00:07<00:03, 815MB/s] pytorch_model-00002-of-00003.bin: 49%|████▉ | 2.45G/5.00G [00:07<00:03, 666MB/s] pytorch_model-00002-of-00003.bin: 52%|█████▏ | 2.58G/5.00G [00:07<00:03, 784MB/s] pytorch_model-00002-of-00003.bin: 53%|█████▎ | 2.67G/5.00G [00:07<00:02, 793MB/s] pytorch_model-00002-of-00003.bin: 57%|█████▋ | 2.83G/5.00G [00:07<00:02, 932MB/s] pytorch_model-00002-of-00003.bin: 59%|█████▊ | 2.94G/5.00G [00:07<00:02, 848MB/s] pytorch_model-00002-of-00003.bin: 68%|██████▊ | 3.39G/5.00G [00:07<00:00, 1.72GB/s] pytorch_model-00002-of-00003.bin: 72%|███████▏ | 3.59G/5.00G [00:08<00:01, 947MB/s] pytorch_model-00002-of-00003.bin: 75%|███████▍ | 3.74G/5.00G [00:08<00:01, 956MB/s] pytorch_model-00002-of-00003.bin: 78%|███████▊ | 3.88G/5.00G [00:08<00:01, 722MB/s] pytorch_model-00002-of-00003.bin: 80%|███████▉ | 4.00G/5.00G [00:09<00:01, 644MB/s] pytorch_model-00002-of-00003.bin: 82%|████████▏ | 4.09G/5.00G [00:09<00:01, 676MB/s] pytorch_model-00002-of-00003.bin: 85%|████████▍ | 4.25G/5.00G [00:09<00:00, 827MB/s] pytorch_model-00002-of-00003.bin: 91%|█████████ | 4.53G/5.00G [00:09<00:00, 1.22GB/s] pytorch_model-00002-of-00003.bin: 94%|█████████▍| 4.70G/5.00G [00:09<00:00, 1.18GB/s] pytorch_model-00002-of-00003.bin: 99%|█████████▉| 4.97G/5.00G [00:09<00:00, 1.52GB/s] pytorch_model-00002-of-00003.bin: 100%|█████████▉| 5.00G/5.00G [00:09<00:00, 517MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: tokenizer_config.json: 0%| | 0.00/1.02k [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 1.02k/1.02k [00:00<00:00, 8.27MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: Downloaded to shared memory in 28.180s
deverdever-heavenly-goat-v5-v2-mkmlizer: quantizing model to /dev/shm/model_cache
deverdever-heavenly-goat-v5-v2-mkmlizer: Saving mkml model at /dev/shm/model_cache
deverdever-heavenly-goat-v5-v2-mkmlizer: Reading /tmp/tmp6wc9uc2v/pytorch_model.bin.index.json
deverdever-heavenly-goat-v5-v2-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:02<11:05, 2.30s/it] Profiling: 34%|███▎ | 98/291 [00:03<00:04, 39.58it/s] Profiling: 70%|███████ | 204/291 [00:03<00:01, 70.96it/s] Profiling: 100%|██████████| 291/291 [00:05<00:00, 70.15it/s] Profiling: 100%|██████████| 291/291 [00:05<00:00, 56.53it/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: quantized model in 15.765s
deverdever-heavenly-goat-v5-v2-mkmlizer: Processed model DeverDever/heavenly-goat-v5 in 44.922s
deverdever-heavenly-goat-v5-v2-mkmlizer: creating bucket guanaco-mkml-models
deverdever-heavenly-goat-v5-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
deverdever-heavenly-goat-v5-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2/config.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2/tokenizer_config.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2/special_tokens_map.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2/tokenizer.model
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2/tokenizer.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/deverdever-heavenly-goat-v5-v2/mkml_model.tensors
deverdever-heavenly-goat-v5-v2-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
deverdever-heavenly-goat-v5-v2-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.
deverdever-heavenly-goat-v5-v2-mkmlizer: warnings.warn(
deverdever-heavenly-goat-v5-v2-mkmlizer: config.json: 0%| | 0.00/1.05k [00:00<?, ?B/s] config.json: 100%|██████████| 1.05k/1.05k [00:00<00:00, 11.8MB/s]
deverdever-heavenly-goat-v5-v2-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.
deverdever-heavenly-goat-v5-v2-mkmlizer: warnings.warn(
deverdever-heavenly-goat-v5-v2-mkmlizer: tokenizer_config.json: 0%| | 0.00/234 [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 234/234 [00:00<00:00, 3.19MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 16.0MB/s]
deverdever-heavenly-goat-v5-v2-mkmlizer: tokenizer.json: 0%| | 0.00/2.11M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 2.11M/2.11M [00:00<00:00, 27.8MB/s]
deverdever-heavenly-goat-v5-v2-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.
deverdever-heavenly-goat-v5-v2-mkmlizer: warnings.warn(
deverdever-heavenly-goat-v5-v2-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
deverdever-heavenly-goat-v5-v2-mkmlizer: Saving duration: 0.247s
deverdever-heavenly-goat-v5-v2-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 7.787s
deverdever-heavenly-goat-v5-v2-mkmlizer: creating bucket guanaco-reward-models
deverdever-heavenly-goat-v5-v2-mkmlizer: Bucket 's3://guanaco-reward-models/' created
deverdever-heavenly-goat-v5-v2-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/config.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/special_tokens_map.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/tokenizer_config.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/vocab.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/merges.txt
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/tokenizer.json
deverdever-heavenly-goat-v5-v2-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/deverdever-heavenly-goat-v5-v2_reward/reward.tensors
Job deverdever-heavenly-goat-v5-v2-mkmlizer completed after 74.87s with status: succeeded
Stopping job with name deverdever-heavenly-goat-v5-v2-mkmlizer
Pipeline stage MKMLizer completed in 78.60s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service deverdever-heavenly-goat-v5-v2
Waiting for inference service deverdever-heavenly-goat-v5-v2 to be ready
Inference service deverdever-heavenly-goat-v5-v2 ready after 40.266125440597534s
Pipeline stage ISVCDeployer completed in 47.87s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.3183581829071045s
Received healthy response to inference request in 0.9688177108764648s
Received healthy response to inference request in 1.138998031616211s
Received healthy response to inference request in 1.010225772857666s
Received healthy response to inference request in 1.082341194152832s
5 requests
0 failed requests
5th percentile: 0.9770993232727051
10th percentile: 0.9853809356689454
20th percentile: 1.0019441604614259
30th percentile: 1.0246488571166992
40th percentile: 1.0534950256347657
50th percentile: 1.082341194152832
60th percentile: 1.1050039291381837
70th percentile: 1.1276666641235351
80th percentile: 1.1748700618743897
90th percentile: 1.246614122390747
95th percentile: 1.2824861526489257
99th percentile: 1.3111837768554688
mean time: 1.1037481784820558
Pipeline stage StressChecker completed in 6.34s
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
deverdever-heavenly-goat-v5_v2 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of deverdever-heavenly-goat-v5_v2
Running pipeline stage ISVCDeleter
Checking if service deverdever-heavenly-goat-v5-v2 is running
Tearing down inference service deverdever-heavenly-goat-v5-v2
Toredown service deverdever-heavenly-goat-v5-v2
Pipeline stage ISVCDeleter completed in 4.79s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key deverdever-heavenly-goat-v5-v2/config.json from bucket guanaco-mkml-models
Deleting key deverdever-heavenly-goat-v5-v2/mkml_model.tensors from bucket guanaco-mkml-models
Deleting key deverdever-heavenly-goat-v5-v2/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key deverdever-heavenly-goat-v5-v2/tokenizer.json from bucket guanaco-mkml-models
Deleting key deverdever-heavenly-goat-v5-v2/tokenizer.model from bucket guanaco-mkml-models
Deleting key deverdever-heavenly-goat-v5-v2/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key deverdever-heavenly-goat-v5-v2_reward/config.json from bucket guanaco-reward-models
Deleting key deverdever-heavenly-goat-v5-v2_reward/merges.txt from bucket guanaco-reward-models
Deleting key deverdever-heavenly-goat-v5-v2_reward/reward.tensors from bucket guanaco-reward-models
Deleting key deverdever-heavenly-goat-v5-v2_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key deverdever-heavenly-goat-v5-v2_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key deverdever-heavenly-goat-v5-v2_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key deverdever-heavenly-goat-v5-v2_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 2.37s
deverdever-heavenly-goat-v5_v2 status is now torndown due to DeploymentManager action