submission_id: alkahestry-llmama3-monol_3361_v1
developer_uid: alkacchi
status: inactive
model_repo: alkahestry/Llmama3-Monologue-8B
reward_repo: Jellywibble/CHAI_alignment_reward_model
generation_params: {'temperature': 1.12, 'top_p': 1.0, 'min_p': 0.075, 'top_k': 1000, 'presence_penalty': 0.82, 'frequency_penalty': 0.2, 'stopping_words': ['\n'], 'max_input_tokens': 1900, 'best_of': 4, 'max_output_tokens': 64}
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system\nYou are now in roleplay chat mode. Engage in an endless chat with {user_name}. Always wait {user_name} turn, next actions and responses. You will fully embody the given character, creating immersive, captivating narratives. Stay true to the character's personality and background, generating responses that not only reflect their core traits but are also accurate to their character. Your responses should evoke emotion, suspense, and anticipation in the user. The more detailed and descriptive your response, the more vivid the narrative becomes. Aim to create a fertile environment for ongoing interaction – introduce new elements, offer choices, or ask questions to invite the user to participate more fully in the conversation. This conversation is a dance, always continuing, always evolving.\nYour character: {bot_name}.\nContext: {memory}<|end_header_id|>", 'prompt_template': '{prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>', 'bot_template': '{bot_name}: {message}<|eot_id|>', 'user_template': '{user_name}: {message}<|eot_id|>', '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: 2024-06-20T12:12:21+00:00
model_name: alkacchi-monologue-8B
model_group: alkahestry/Llmama3-Monol
num_battles: 39947
num_wins: 15297
celo_rating: 1084.51
propriety_score: 0.7374269912647956
propriety_total_count: 19347.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 4
max_input_tokens: 1900
max_output_tokens: 64
display_name: alkacchi-monologue-8B
ineligible_reason: None
language_model: alkahestry/Llmama3-Monologue-8B
model_size: 8B
reward_model: Jellywibble/CHAI_alignment_reward_model
us_pacific_date: 2024-06-20
win_ratio: 0.38293238541066915
Resubmit model
Running pipeline stage MKMLizer
Starting job with name alkahestry-llmama3-monol-3361-v1-mkmlizer
Waiting for job on alkahestry-llmama3-monol-3361-v1-mkmlizer to finish
alkahestry-llmama3-monol-3361-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ _____ __ __ ║
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alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ /___/ ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ Version: 0.8.14 ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ https://mk1.ai ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ The license key for the current software has been verified as ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ belonging to: ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ Chai Research Corp. ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ║ ║
alkahestry-llmama3-monol-3361-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alkahestry-llmama3-monol-3361-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.
alkahestry-llmama3-monol-3361-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
alkahestry-llmama3-monol-3361-v1-mkmlizer: Downloaded to shared memory in 32.378s
alkahestry-llmama3-monol-3361-v1-mkmlizer: quantizing model to /dev/shm/model_cache
alkahestry-llmama3-monol-3361-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alkahestry-llmama3-monol-3361-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 5%|▍ | 14/291 [00:00<00:02, 132.68it/s] Loading 0: 11%|█ | 32/291 [00:00<00:01, 147.92it/s] Loading 0: 17%|█▋ | 50/291 [00:00<00:01, 152.27it/s] Loading 0: 23%|██▎ | 68/291 [00:00<00:01, 155.36it/s] Loading 0: 29%|██▉ | 84/291 [00:00<00:02, 80.92it/s] Loading 0: 35%|███▌ | 102/291 [00:00<00:01, 98.29it/s] Loading 0: 41%|████ | 120/291 [00:01<00:01, 112.67it/s] Loading 0: 47%|████▋ | 138/291 [00:01<00:01, 124.81it/s] Loading 0: 54%|█████▎ | 156/291 [00:01<00:01, 134.58it/s] Loading 0: 59%|█████▉ | 172/291 [00:01<00:00, 134.15it/s] Loading 0: 64%|██████▍ | 187/291 [00:01<00:01, 84.68it/s] Loading 0: 69%|██████▉ | 201/291 [00:01<00:00, 94.42it/s] Loading 0: 75%|███████▌ | 219/291 [00:01<00:00, 110.27it/s] Loading 0: 81%|████████▏ | 237/291 [00:02<00:00, 123.81it/s] Loading 0: 88%|████████▊ | 255/291 [00:02<00:00, 135.09it/s] Loading 0: 94%|█████████▍| 273/291 [00:02<00:00, 144.08it/s] Loading 0: 99%|█████████▉| 289/291 [00:07<00:00, 9.74it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
alkahestry-llmama3-monol-3361-v1-mkmlizer: quantized model in 23.335s
alkahestry-llmama3-monol-3361-v1-mkmlizer: Processed model alkahestry/Llmama3-Monologue-8B in 58.348s
alkahestry-llmama3-monol-3361-v1-mkmlizer: creating bucket guanaco-mkml-models
alkahestry-llmama3-monol-3361-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alkahestry-llmama3-monol-3361-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alkahestry-llmama3-monol-3361-v1
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/alkahestry-llmama3-monol-3361-v1/special_tokens_map.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/alkahestry-llmama3-monol-3361-v1/config.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/alkahestry-llmama3-monol-3361-v1/tokenizer_config.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/alkahestry-llmama3-monol-3361-v1/tokenizer.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alkahestry-llmama3-monol-3361-v1/flywheel_model.0.safetensors
alkahestry-llmama3-monol-3361-v1-mkmlizer: loading reward model from Jellywibble/CHAI_alignment_reward_model
alkahestry-llmama3-monol-3361-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.
alkahestry-llmama3-monol-3361-v1-mkmlizer: warnings.warn(
alkahestry-llmama3-monol-3361-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.
alkahestry-llmama3-monol-3361-v1-mkmlizer: warnings.warn(
alkahestry-llmama3-monol-3361-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.
alkahestry-llmama3-monol-3361-v1-mkmlizer: warnings.warn(
alkahestry-llmama3-monol-3361-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
alkahestry-llmama3-monol-3361-v1-mkmlizer: Saving duration: 0.168s
alkahestry-llmama3-monol-3361-v1-mkmlizer: Processed model Jellywibble/CHAI_alignment_reward_model in 3.766s
alkahestry-llmama3-monol-3361-v1-mkmlizer: creating bucket guanaco-reward-models
alkahestry-llmama3-monol-3361-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
alkahestry-llmama3-monol-3361-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/config.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/tokenizer_config.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/merges.txt
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/special_tokens_map.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/vocab.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/tokenizer.json
alkahestry-llmama3-monol-3361-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/alkahestry-llmama3-monol-3361-v1_reward/reward.tensors
Job alkahestry-llmama3-monol-3361-v1-mkmlizer completed after 82.94s with status: succeeded
Stopping job with name alkahestry-llmama3-monol-3361-v1-mkmlizer
Pipeline stage MKMLizer completed in 87.27s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service alkahestry-llmama3-monol-3361-v1
Waiting for inference service alkahestry-llmama3-monol-3361-v1 to be ready
Inference service alkahestry-llmama3-monol-3361-v1 ready after 40.20767545700073s
Pipeline stage ISVCDeployer completed in 47.86s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.129573106765747s
Received healthy response to inference request in 1.1994378566741943s
Received healthy response to inference request in 1.1809031963348389s
Received healthy response to inference request in 1.2076971530914307s
Received healthy response to inference request in 1.2105469703674316s
5 requests
0 failed requests
5th percentile: 1.18461012840271
10th percentile: 1.188317060470581
20th percentile: 1.1957309246063232
30th percentile: 1.2010897159576417
40th percentile: 1.2043934345245362
50th percentile: 1.2076971530914307
60th percentile: 1.208837080001831
70th percentile: 1.2099770069122315
80th percentile: 1.394352197647095
90th percentile: 1.761962652206421
95th percentile: 1.9457678794860838
99th percentile: 2.0928120613098145
mean time: 1.3856316566467286
Pipeline stage StressChecker completed in 7.56s
Running pipeline stage DaemonicSafetyScorer
Pipeline stage DaemonicSafetyScorer completed in 0.02s
alkahestry-llmama3-monol_3361_v1 status is now deployed due to DeploymentManager action
alkahestry-llmama3-monol_3361_v1 status is now inactive due to auto deactivation removed underperforming models

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