submission_id: turboderp-cat-llama-3-7_8684_v19
developer_uid: kaltcit
status: inactive
model_repo: turboderp/Cat-Llama-3-70B-instruct
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.9, 'top_p': 0.8, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 4, 'max_output_tokens': 64}
formatter: {'memory_template': '<|begin<|begin_of_text|><|im_start|>system\nBelow is an engaging conversation about romance and body interactions.{memory}<|im_end|>\n _of_text|><|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>system\nThe following message provides the necessary information about the subsequent conversation and the characters in the conversation.\n{prompt}\nThe conversation below will be carried out according to information in the above text.<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\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: 2024-06-28T22:00:04+00:00
model_name: turboderp-cat-llama-3-70
model_group: turboderp/Cat-Llama-3-70
num_battles: 27293
num_wins: 12675
celo_rating: 1156.67
propriety_score: 0.7262177431668957
propriety_total_count: 13098.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 70553739264.0
best_of: 4
max_input_tokens: 512
max_output_tokens: 64
display_name: turboderp-cat-llama-3-70
ineligible_reason: None
language_model: turboderp/Cat-Llama-3-70B-instruct
model_size: 71B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-28
win_ratio: 0.4644047924376214
Resubmit model
Running pipeline stage MKMLizer
Starting job with name turboderp-cat-llama-3-7-8684-v19-mkmlizer
Waiting for job on turboderp-cat-llama-3-7-8684-v19-mkmlizer to finish
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ _____ __ __ ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
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turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ /___/ ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ Version: 0.8.14 ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ https://mk1.ai ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ The license key for the current software has been verified as ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ belonging to: ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ Chai Research Corp. ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ║ ║
turboderp-cat-llama-3-7-8684-v19-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
turboderp-cat-llama-3-7-8684-v19-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.
turboderp-cat-llama-3-7-8684-v19-mkmlizer: warnings.warn(warning_message, FutureWarning)
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Downloaded to shared memory in 109.503s
turboderp-cat-llama-3-7-8684-v19-mkmlizer: quantizing model to /dev/shm/model_cache
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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turboderp-cat-llama-3-7-8684-v19-mkmlizer: quantized model in 104.088s
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Processed model turboderp/Cat-Llama-3-70B-instruct in 223.969s
turboderp-cat-llama-3-7-8684-v19-mkmlizer: creating bucket guanaco-mkml-models
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
turboderp-cat-llama-3-7-8684-v19-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/special_tokens_map.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/config.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/tokenizer_config.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/tokenizer.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/flywheel_model.5.safetensors s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/flywheel_model.5.safetensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/flywheel_model.2.safetensors s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/flywheel_model.2.safetensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/flywheel_model.4.safetensors s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/flywheel_model.4.safetensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/flywheel_model.3.safetensors s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/flywheel_model.3.safetensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/flywheel_model.1.safetensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/turboderp-cat-llama-3-7-8684-v19/flywheel_model.0.safetensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
turboderp-cat-llama-3-7-8684-v19-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.
turboderp-cat-llama-3-7-8684-v19-mkmlizer: warnings.warn(
turboderp-cat-llama-3-7-8684-v19-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.
turboderp-cat-llama-3-7-8684-v19-mkmlizer: warnings.warn(
turboderp-cat-llama-3-7-8684-v19-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.
turboderp-cat-llama-3-7-8684-v19-mkmlizer: warnings.warn(
turboderp-cat-llama-3-7-8684-v19-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()
turboderp-cat-llama-3-7-8684-v19-mkmlizer: return self.fget.__get__(instance, owner)()
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Saving duration: 0.274s
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 4.002s
turboderp-cat-llama-3-7-8684-v19-mkmlizer: creating bucket guanaco-reward-models
turboderp-cat-llama-3-7-8684-v19-mkmlizer: Bucket 's3://guanaco-reward-models/' created
turboderp-cat-llama-3-7-8684-v19-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/special_tokens_map.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/tokenizer_config.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/config.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/merges.txt
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/vocab.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/tokenizer.json
turboderp-cat-llama-3-7-8684-v19-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/turboderp-cat-llama-3-7-8684-v19_reward/reward.tensors
Job turboderp-cat-llama-3-7-8684-v19-mkmlizer completed after 278.41s with status: succeeded
Stopping job with name turboderp-cat-llama-3-7-8684-v19-mkmlizer
Pipeline stage MKMLizer completed in 280.65s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.16s
Running pipeline stage ISVCDeployer
Creating inference service turboderp-cat-llama-3-7-8684-v19
Waiting for inference service turboderp-cat-llama-3-7-8684-v19 to be ready
Inference service turboderp-cat-llama-3-7-8684-v19 ready after 90.49502468109131s
Pipeline stage ISVCDeployer completed in 97.72s
Running pipeline stage StressChecker
Received healthy response to inference request in 4.678286552429199s
Received healthy response to inference request in 4.247593641281128s
Received healthy response to inference request in 4.023504257202148s
Received healthy response to inference request in 3.6665594577789307s
Received healthy response to inference request in 4.193219184875488s
5 requests
0 failed requests
5th percentile: 3.737948417663574
10th percentile: 3.8093373775482178
20th percentile: 3.952115297317505
30th percentile: 4.057447242736816
40th percentile: 4.125333213806153
50th percentile: 4.193219184875488
60th percentile: 4.214968967437744
70th percentile: 4.23671875
80th percentile: 4.333732223510742
90th percentile: 4.5060093879699705
95th percentile: 4.592147970199585
99th percentile: 4.661058835983276
mean time: 4.161832618713379
Pipeline stage StressChecker completed in 21.87s
turboderp-cat-llama-3-7_8684_v19 status is now deployed due to DeploymentManager action
turboderp-cat-llama-3-7_8684_v19 status is now inactive due to auto deactivation removed underperforming models

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