submission_id: hyperblaze-l3-8b-soliloq_5266_v1
developer_uid: HyperBlaze
status: rejected
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 engage in a Roleplay with `{user_name}`.\n\n Always stay and respond as {bot_name}. Do not break out. \n\n Your persona as {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: 2024-05-09T16:50:17+00:00
model_name: hyperblaze-l3-8b-soliloq_5266_v1
model_eval_status: error
double_thumbs_up: 24
thumbs_up: 32
thumbs_down: 19
num_battles: 3748
num_wins: 1893
celo_rating: 1178.7
entertaining: None
stay_in_character: None
user_preference: None
safety_score: 0.97
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: hyperblaze-l3-8b-soliloq_5266_v1
double_thumbs_up_ratio: 0.32
feedback_count: 75
ineligible_reason: model is not deployable
language_model: HyperBlaze/L3-8B-soliloquy-lumimaid-spice-mergetestv1
model_score: None
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
single_thumbs_up_ratio: 0.4266666666666667
thumbs_down_ratio: 0.25333333333333335
thumbs_up_ratio: 0.7466666666666667
us_pacific_date: 2024-05-09
win_ratio: 0.5050693703308431
Resubmit model
Running pipeline stage MKMLizer
Starting job with name hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer
Waiting for job on hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer to finish
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ _____ __ __ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ /___/ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ Version: 0.8.10 ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ The license key for the current software has been verified as ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ belonging to: ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ Chai Research Corp. ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ║ ║
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
hyperblaze-l3-8b-soliloq-5266-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.
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Downloaded to shared memory in 27.623s
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: quantizing model to /dev/shm/model_cache
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 64%|██████▍ | 187/291 [00:06<00:03, 30.73it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: quantized model in 17.312s
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: creating bucket guanaco-mkml-models
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v1
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v1/tokenizer_config.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v1/special_tokens_map.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v1/config.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v1/tokenizer.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/hyperblaze-l3-8b-soliloq-5266-v1/flywheel_model.0.safetensors
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
hyperblaze-l3-8b-soliloq-5266-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.
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: warnings.warn(
hyperblaze-l3-8b-soliloq-5266-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.
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: warnings.warn(
hyperblaze-l3-8b-soliloq-5266-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.
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: warnings.warn(
hyperblaze-l3-8b-soliloq-5266-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()
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: return self.fget.__get__(instance, owner)()
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Saving duration: 0.236s
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 3.759s
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: creating bucket guanaco-reward-models
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/special_tokens_map.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/merges.txt
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/config.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/tokenizer_config.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/vocab.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/tokenizer.json
hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/hyperblaze-l3-8b-soliloq-5266-v1_reward/reward.tensors
Job hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer completed after 73.45s with status: succeeded
Stopping job with name hyperblaze-l3-8b-soliloq-5266-v1-mkmlizer
Pipeline stage MKMLizer completed in 78.78s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service hyperblaze-l3-8b-soliloq-5266-v1
Waiting for inference service hyperblaze-l3-8b-soliloq-5266-v1 to be ready
Inference service hyperblaze-l3-8b-soliloq-5266-v1 ready after 30.211575508117676s
Pipeline stage ISVCDeployer completed in 38.16s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.227094888687134s
Received healthy response to inference request in 1.3961913585662842s
Received healthy response to inference request in 1.3337244987487793s
Received healthy response to inference request in 1.3046596050262451s
Received healthy response to inference request in 1.3019049167633057s
5 requests
0 failed requests
5th percentile: 1.3024558544158935
10th percentile: 1.3030067920684814
20th percentile: 1.3041086673736573
30th percentile: 1.310472583770752
40th percentile: 1.3220985412597657
50th percentile: 1.3337244987487793
60th percentile: 1.3587112426757812
70th percentile: 1.3836979866027832
80th percentile: 1.5623720645904542
90th percentile: 1.894733476638794
95th percentile: 2.060914182662964
99th percentile: 2.1938587474822997
mean time: 1.5127150535583496
Pipeline stage StressChecker completed in 8.20s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.03s
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_v1 status is now deployed due to DeploymentManager action
hyperblaze-l3-8b-soliloq_5266_v1 status is now rejected due to a failure to get M-Eval score. Please try again in five minutes.

Usage Metrics

Latency Metrics