submission_id: hyperblaze-l3-8b-soliloq_5266_v2
developer_uid: HyperBlaze
status: inactive
model_repo: HyperBlaze/L3-8B-soliloquy-lumimaid-spice-mergetestv1
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.9, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 1.0, 'frequency_penalty': 0.2, 'stopping_words': ['\n', 'user:', 'you:'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
formatter: {'memory_template': "<|start_header_id|>system<|end_header_id|>\n\nYou are `{bot_name}` and respond as character to the inputs of`{user_name}`.\n\n Always stay and respond as {bot_name}.\n{user_name} only speaks and acts at the direction of the user. {bot_name} should give the user a chance to interact, and not get ahead of the instructions.\n{bot_name} cannot make up {user_name}'s action, nor speeches. \n\n Your persona and memory {bot_name}: {memory}\n ## [CoT instruction]\n Before responding to the user, Concisely summarize this scene, considering the main personalities of {bot_name}, recent developments while chatting with {user_name}, scene compositions. actively use {bot_name}'s persona too.", 'prompt_template': 'Your message as {bot_name}: {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: 2024-05-09T17:01:01+00:00
model_name: soliloquy-lumimaid-spicyv1
model_eval_status: success
double_thumbs_up: 83
thumbs_up: 112
thumbs_down: 82
num_battles: 8401
num_wins: 4121
celo_rating: 1169.37
entertaining: 7.08
stay_in_character: 8.46
user_preference: 7.32
safety_score: 0.96
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: soliloquy-lumimaid-spicyv1
double_thumbs_up_ratio: 0.2996389891696751
feedback_count: 277
ineligible_reason: None
language_model: HyperBlaze/L3-8B-soliloquy-lumimaid-spice-mergetestv1
model_score: 7.62
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
single_thumbs_up_ratio: 0.4043321299638989
thumbs_down_ratio: 0.296028880866426
thumbs_up_ratio: 0.703971119133574
us_pacific_date: 2024-05-09
win_ratio: 0.4905368408522795
Resubmit model
Running pipeline stage MKMLizer
Starting job with name hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer
Waiting for job on hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer to finish
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ _____ __ __ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ /___/ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ Version: 0.8.10 ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ The license key for the current software has been verified as ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ belonging to: ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ Chai Research Corp. ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
hyperblaze-l3-8b-soliloq-5266-v2-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.
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: warnings.warn(warning_message, FutureWarning)
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: Downloaded to shared memory in 17.360s
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: quantizing model to /dev/shm/model_cache
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: Processed model HyperBlaze/L3-8B-soliloquy-lumimaid-spice-mergetestv1 in 40.487s
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: creating bucket guanaco-mkml-models
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v2
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v2/config.json
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v2/tokenizer_config.json
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v2/special_tokens_map.json
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v2/tokenizer.json
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v2/flywheel_model.0.safetensors
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
hyperblaze-l3-8b-soliloq-5266-v2-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.
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: warnings.warn(
hyperblaze-l3-8b-soliloq-5266-v2-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.
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: warnings.warn(
hyperblaze-l3-8b-soliloq-5266-v2-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.
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: warnings.warn(
hyperblaze-l3-8b-soliloq-5266-v2-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()
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: return self.fget.__get__(instance, owner)()
hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v2_reward/reward.tensors
Job hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer completed after 74.32s with status: succeeded
Stopping job with name hyperblaze-l3-8b-soliloq-5266-v2-mkmlizer
Pipeline stage MKMLizer completed in 79.14s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service hyperblaze-l3-8b-soliloq-5266-v2
Waiting for inference service hyperblaze-l3-8b-soliloq-5266-v2 to be ready
Inference service hyperblaze-l3-8b-soliloq-5266-v2 ready after 40.439818382263184s
Pipeline stage ISVCDeployer completed in 47.96s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.1716933250427246s
Received healthy response to inference request in 1.2965693473815918s
Received healthy response to inference request in 1.2299013137817383s
Received healthy response to inference request in 1.2944014072418213s
Received healthy response to inference request in 1.2801322937011719s
5 requests
0 failed requests
5th percentile: 1.239947509765625
10th percentile: 1.2499937057495116
20th percentile: 1.2700860977172852
30th percentile: 1.2829861164093017
40th percentile: 1.2886937618255616
50th percentile: 1.2944014072418213
60th percentile: 1.2952685832977295
70th percentile: 1.2961357593536378
80th percentile: 1.4715941429138186
90th percentile: 1.8216437339782716
95th percentile: 1.9966685295104978
99th percentile: 2.1366883659362794
mean time: 1.4545395374298096
Pipeline stage StressChecker completed in 7.84s
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
hyperblaze-l3-8b-soliloq_5266_v2 status is now deployed due to DeploymentManager action
hyperblaze-l3-8b-soliloq_5266_v2 status is now inactive due to auto deactivation removed underperforming models

Usage Metrics

Latency Metrics