submission_id: v000000-l3-8b-megaserpentine_v4
developer_uid: v000000
status: inactive
model_repo: v000000/L3-8B-MegaSerpentine
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.3, 'top_p': 0.95, 'min_p': 0.08, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, '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}
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}:', 'truncate_by_message': False}
timestamp: 2024-06-18T07:43:27+00:00
model_name: v000000-l3-8b-megaserpentine_v4
model_group: v000000/L3-8B-MegaSerpen
num_battles: 20220
num_wins: 10436
celo_rating: 1209.1
propriety_score: 0.692902029463274
propriety_total_count: 9707.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: v000000-l3-8b-megaserpentine_v4
ineligible_reason: None
language_model: v000000/L3-8B-MegaSerpentine
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-18
win_ratio: 0.5161226508407517
Resubmit model
Running pipeline stage MKMLizer
Starting job with name v000000-l3-8b-megaserpentine-v4-mkmlizer
Waiting for job on v000000-l3-8b-megaserpentine-v4-mkmlizer to finish
v000000-l3-8b-megaserpentine-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ _____ __ __ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ /___/ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ Version: 0.8.14 ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ https://mk1.ai ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ The license key for the current software has been verified as ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ belonging to: ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ Chai Research Corp. ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
v000000-l3-8b-megaserpentine-v4-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.
v000000-l3-8b-megaserpentine-v4-mkmlizer: warnings.warn(warning_message, FutureWarning)
v000000-l3-8b-megaserpentine-v4-mkmlizer: Downloaded to shared memory in 17.856s
v000000-l3-8b-megaserpentine-v4-mkmlizer: quantizing model to /dev/shm/model_cache
v000000-l3-8b-megaserpentine-v4-mkmlizer: Saving flywheel model at /dev/shm/model_cache
v000000-l3-8b-megaserpentine-v4-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 1%| | 2/291 [00:04<10:54, 2.27s/it] Loading 0: 5%|▌ | 15/291 [00:04<01:02, 4.40it/s] Loading 0: 11%|█▏ | 33/291 [00:04<00:22, 11.68it/s] Loading 0: 18%|█▊ | 51/291 [00:04<00:11, 21.01it/s] Loading 0: 22%|██▏ | 65/291 [00:05<00:09, 25.04it/s] Loading 0: 27%|██▋ | 79/291 [00:05<00:06, 34.39it/s] Loading 0: 33%|███▎ | 96/291 [00:05<00:04, 48.04it/s] Loading 0: 39%|███▉ | 114/291 [00:05<00:02, 64.14it/s] Loading 0: 45%|████▌ | 132/291 [00:05<00:01, 80.85it/s] Loading 0: 52%|█████▏ | 150/291 [00:05<00:01, 96.23it/s] Loading 0: 57%|█████▋ | 166/291 [00:06<00:01, 73.45it/s] Loading 0: 63%|██████▎ | 182/291 [00:06<00:01, 87.29it/s] Loading 0: 67%|██████▋ | 196/291 [00:06<00:00, 96.92it/s] Loading 0: 73%|███████▎ | 213/291 [00:06<00:00, 110.97it/s] Loading 0: 79%|███████▉ | 231/291 [00:06<00:00, 124.98it/s] Loading 0: 86%|████████▌ | 249/291 [00:06<00:00, 133.59it/s] Loading 0: 91%|█████████▏| 266/291 [00:06<00:00, 86.21it/s] Loading 0: 97%|█████████▋| 283/291 [00:07<00:00, 100.32it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
v000000-l3-8b-megaserpentine-v4-mkmlizer: quantized model in 23.429s
v000000-l3-8b-megaserpentine-v4-mkmlizer: Processed model v000000/L3-8B-MegaSerpentine in 43.963s
v000000-l3-8b-megaserpentine-v4-mkmlizer: creating bucket guanaco-mkml-models
v000000-l3-8b-megaserpentine-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
v000000-l3-8b-megaserpentine-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v4
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v4/config.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v4/tokenizer_config.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v4/special_tokens_map.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v4/tokenizer.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
v000000-l3-8b-megaserpentine-v4-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.
v000000-l3-8b-megaserpentine-v4-mkmlizer: warnings.warn(
v000000-l3-8b-megaserpentine-v4-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.
v000000-l3-8b-megaserpentine-v4-mkmlizer: warnings.warn(
v000000-l3-8b-megaserpentine-v4-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.
v000000-l3-8b-megaserpentine-v4-mkmlizer: warnings.warn(
v000000-l3-8b-megaserpentine-v4-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()
v000000-l3-8b-megaserpentine-v4-mkmlizer: return self.fget.__get__(instance, owner)()
v000000-l3-8b-megaserpentine-v4-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
v000000-l3-8b-megaserpentine-v4-mkmlizer: Saving duration: 0.412s
v000000-l3-8b-megaserpentine-v4-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 3.764s
v000000-l3-8b-megaserpentine-v4-mkmlizer: creating bucket guanaco-reward-models
v000000-l3-8b-megaserpentine-v4-mkmlizer: Bucket 's3://guanaco-reward-models/' created
v000000-l3-8b-megaserpentine-v4-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/special_tokens_map.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/tokenizer_config.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/config.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/merges.txt
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/vocab.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/tokenizer.json
v000000-l3-8b-megaserpentine-v4-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v4_reward/reward.tensors
Job v000000-l3-8b-megaserpentine-v4-mkmlizer completed after 72.74s with status: succeeded
Stopping job with name v000000-l3-8b-megaserpentine-v4-mkmlizer
Pipeline stage MKMLizer completed in 73.52s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service v000000-l3-8b-megaserpentine-v4
Waiting for inference service v000000-l3-8b-megaserpentine-v4 to be ready
Inference service v000000-l3-8b-megaserpentine-v4 ready after 110.67683172225952s
Pipeline stage ISVCDeployer completed in 116.47s
Running pipeline stage StressChecker
%s, retrying in %s seconds...
Received healthy response to inference request in 2.3183517456054688s
Received healthy response to inference request in 1.284388542175293s
Received healthy response to inference request in 1.2439086437225342s
Received healthy response to inference request in 1.2742772102355957s
%s, retrying in %s seconds...
Received healthy response to inference request in 1.3143126964569092s
Received healthy response to inference request in 1.275404691696167s
Received healthy response to inference request in 1.1367220878601074s
Received healthy response to inference request in 1.2510371208190918s
Received healthy response to inference request in 1.2682204246520996s
5 requests
0 failed requests
5th percentile: 1.1595850944519044
10th percentile: 1.1824481010437011
20th percentile: 1.2281741142272948
30th percentile: 1.2544737815856934
40th percentile: 1.2613471031188965
50th percentile: 1.2682204246520996
60th percentile: 1.2710941314697266
70th percentile: 1.2739678382873536
80th percentile: 1.2831862926483155
90th percentile: 1.2987494945526123
95th percentile: 1.3065310955047607
99th percentile: 1.3127563762664796
mean time: 1.249139404296875
Pipeline stage StressChecker completed in 53.24s
Running pipeline stage DaemonicSafetyScorer
Pipeline stage DaemonicSafetyScorer completed in 0.03s
v000000-l3-8b-megaserpentine_v4 status is now deployed due to DeploymentManager action
v000000-l3-8b-megaserpentine_v4 status is now inactive due to auto deactivation removed underperforming models

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