submission_id: v000000-l3-8b-megaserpentine_v1
developer_uid: v000000
status: inactive
model_repo: v000000/L3-8B-MegaSerpentine
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.1, 'top_p': 0.73, 'min_p': 0.11, 'top_k': 190, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '{user_name}:', '<|eot_id|>', '<|end_of_text|>'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{bot_name}'s Persona: {memory}\n\n", 'prompt_template': '{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}: {message}<|eot_id|>', 'user_template': '<|start_header_id|>user<|end_header_id|>\n\n{user_name}: {message}<|eot_id|>', 'response_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{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: 2024-06-18T07:29:15+00:00
model_name: v000000-l3-8b-megaserpentine_v1
model_group: v000000/L3-8B-MegaSerpen
num_battles: 12780
num_wins: 6626
celo_rating: 1209.84
propriety_score: 0.7062652563059398
propriety_total_count: 6145.0
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_v1
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: 0.5184663536776213
Resubmit model
Running pipeline stage MKMLizer
Starting job with name v000000-l3-8b-megaserpentine-v1-mkmlizer
Waiting for job on v000000-l3-8b-megaserpentine-v1-mkmlizer to finish
v000000-l3-8b-megaserpentine-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ _____ __ __ ║
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v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
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v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ /___/ ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ Version: 0.8.14 ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ https://mk1.ai ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ The license key for the current software has been verified as ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ belonging to: ║
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v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ Chai Research Corp. ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ║ ║
v000000-l3-8b-megaserpentine-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
v000000-l3-8b-megaserpentine-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.
v000000-l3-8b-megaserpentine-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
v000000-l3-8b-megaserpentine-v1-mkmlizer: Downloaded to shared memory in 26.720s
v000000-l3-8b-megaserpentine-v1-mkmlizer: quantizing model to /dev/shm/model_cache
v000000-l3-8b-megaserpentine-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
v000000-l3-8b-megaserpentine-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 1%| | 2/291 [00:04<10:51, 2.26s/it] Loading 0: 5%|▌ | 15/291 [00:04<01:02, 4.42it/s] Loading 0: 11%|█▏ | 33/291 [00:04<00:21, 11.73it/s] Loading 0: 18%|█▊ | 51/291 [00:04<00:11, 21.10it/s] Loading 0: 22%|██▏ | 65/291 [00:05<00:08, 25.11it/s] Loading 0: 28%|██▊ | 81/291 [00:05<00:05, 36.01it/s] Loading 0: 33%|███▎ | 96/291 [00:05<00:04, 47.81it/s] Loading 0: 39%|███▉ | 114/291 [00:05<00:02, 63.94it/s] Loading 0: 45%|████▌ | 132/291 [00:05<00:01, 81.01it/s] Loading 0: 52%|█████▏ | 150/291 [00:05<00:01, 96.47it/s] Loading 0: 57%|█████▋ | 166/291 [00:06<00:01, 74.95it/s] Loading 0: 63%|██████▎ | 184/291 [00:06<00:01, 91.20it/s] Loading 0: 69%|██████▉ | 202/291 [00:06<00:00, 106.67it/s] Loading 0: 76%|███████▌ | 220/291 [00:06<00:00, 119.80it/s] Loading 0: 82%|████████▏ | 238/291 [00:06<00:00, 131.91it/s] Loading 0: 88%|████████▊ | 256/291 [00:06<00:00, 141.92it/s] Loading 0: 94%|█████████▍| 273/291 [00:06<00:00, 94.69it/s] Loading 0: 99%|█████████▉| 289/291 [00:07<00:00, 106.40it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
v000000-l3-8b-megaserpentine-v1-mkmlizer: quantized model in 23.119s
v000000-l3-8b-megaserpentine-v1-mkmlizer: Processed model v000000/L3-8B-MegaSerpentine in 52.435s
v000000-l3-8b-megaserpentine-v1-mkmlizer: creating bucket guanaco-mkml-models
v000000-l3-8b-megaserpentine-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
v000000-l3-8b-megaserpentine-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v1
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v1/config.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v1/tokenizer_config.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v1/special_tokens_map.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v1/tokenizer.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/v000000-l3-8b-megaserpentine-v1/flywheel_model.0.safetensors
v000000-l3-8b-megaserpentine-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
v000000-l3-8b-megaserpentine-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.
v000000-l3-8b-megaserpentine-v1-mkmlizer: warnings.warn(
v000000-l3-8b-megaserpentine-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.
v000000-l3-8b-megaserpentine-v1-mkmlizer: warnings.warn(
v000000-l3-8b-megaserpentine-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.
v000000-l3-8b-megaserpentine-v1-mkmlizer: warnings.warn(
v000000-l3-8b-megaserpentine-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()
v000000-l3-8b-megaserpentine-v1-mkmlizer: return self.fget.__get__(instance, owner)()
v000000-l3-8b-megaserpentine-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
v000000-l3-8b-megaserpentine-v1-mkmlizer: Saving duration: 0.410s
v000000-l3-8b-megaserpentine-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 7.540s
v000000-l3-8b-megaserpentine-v1-mkmlizer: creating bucket guanaco-reward-models
v000000-l3-8b-megaserpentine-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
v000000-l3-8b-megaserpentine-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/config.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/merges.txt
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/tokenizer_config.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/special_tokens_map.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/vocab.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/tokenizer.json
v000000-l3-8b-megaserpentine-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/v000000-l3-8b-megaserpentine-v1_reward/reward.tensors
Job v000000-l3-8b-megaserpentine-v1-mkmlizer completed after 82.82s with status: succeeded
Stopping job with name v000000-l3-8b-megaserpentine-v1-mkmlizer
Pipeline stage MKMLizer completed in 86.15s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service v000000-l3-8b-megaserpentine-v1
Waiting for inference service v000000-l3-8b-megaserpentine-v1 to be ready
Inference service v000000-l3-8b-megaserpentine-v1 ready after 40.369771003723145s
Pipeline stage ISVCDeployer completed in 47.49s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.1899313926696777s
Received healthy response to inference request in 1.3574907779693604s
Received healthy response to inference request in 1.3144116401672363s
Received healthy response to inference request in 1.2914743423461914s
Received healthy response to inference request in 1.339257001876831s
5 requests
0 failed requests
5th percentile: 1.2960618019104004
10th percentile: 1.3006492614746095
20th percentile: 1.3098241806030273
30th percentile: 1.3193807125091552
40th percentile: 1.3293188571929933
50th percentile: 1.339257001876831
60th percentile: 1.3465505123138428
70th percentile: 1.3538440227508546
80th percentile: 1.523978900909424
90th percentile: 1.8569551467895509
95th percentile: 2.023443269729614
99th percentile: 2.156633768081665
mean time: 1.4985130310058594
Pipeline stage StressChecker completed in 8.12s
Running pipeline stage DaemonicSafetyScorer
Pipeline stage DaemonicSafetyScorer completed in 0.03s
v000000-l3-8b-megaserpentine_v1 status is now deployed due to DeploymentManager action
v000000-l3-8b-megaserpentine_v1 status is now inactive due to auto deactivation removed underperforming models

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