developer_uid: robert_irvine
submission_id: mistralai-mixtral-8x7b-_3473_v77
model_name: mistralai-mixtral-8x7b-_3473_v77
model_group: mistralai/Mixtral-8x7B-I
status: torndown
timestamp: 2024-07-11T18:52:56+00:00
num_battles: 40029
num_wins: 18576
celo_rating: 1166.86
family_friendly_score: 0.0
submission_type: basic
model_repo: mistralai/Mixtral-8x7B-Instruct-v0.1
model_architecture: MixtralForCausalLM
reward_repo: ChaiML/gpt2_medium_pairwise_60m_step_937500
model_num_parameters: 46702792704.0
best_of: 4
max_input_tokens: 512
max_output_tokens: 64
display_name: mistralai-mixtral-8x7b-_3473_v77
is_internal_developer: True
language_model: mistralai/Mixtral-8x7B-Instruct-v0.1
model_size: 47B
ranking_group: single
us_pacific_date: 2024-07-11
win_ratio: 0.46406355392340554
generation_params: {'temperature': 0.9, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 50, 'presence_penalty': 0.5, 'frequency_penalty': 0.5, 'stopping_words': ['\n', '</s>', '<|user|>', '###'], 'max_input_tokens': 512, 'best_of': 4, 'max_output_tokens': 64}
formatter: {'memory_template': '<s>[INST] This is an entertaining conversation. You are {bot_name} who has the persona: {memory}.\nEngage in a chat with {user_name} while staying in character. Try to flirt with {user_name}. Engage in *roleplay* actions. Describe the scene dramatically. \n', 'prompt_template': '{prompt}\n', 'bot_template': '{bot_name}: {message}</s>', 'user_template': '[INST] {user_name}: {message} [/INST]', 'response_template': '{bot_name}:', 'truncate_by_message': False}
reward_formatter: {'bot_template': 'Bot: {message}\n', 'memory_template': '""', 'prompt_template': '""', 'response_template': 'Bot:', 'truncate_by_message': False, 'user_template': 'User: {message}\n'}
Resubmit model
Running pipeline stage MKMLizer
Starting job with name mistralai-mixtral-8x7b-3473-v77-mkmlizer
Waiting for job on mistralai-mixtral-8x7b-3473-v77-mkmlizer to finish
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ _____ __ __ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ /___/ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ Version: 0.8.14 ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ https://mk1.ai ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ The license key for the current software has been verified as ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ belonging to: ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ Chai Research Corp. ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ║ ║
mistralai-mixtral-8x7b-3473-v77-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Downloaded to shared memory in 254.795s
mistralai-mixtral-8x7b-3473-v77-mkmlizer: quantizing model to /dev/shm/model_cache
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mixtral-8x7b-3473-v77-mkmlizer: quantized model in 97.656s
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Processed model mistralai/Mixtral-8x7B-Instruct-v0.1 in 352.451s
mistralai-mixtral-8x7b-3473-v77-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mixtral-8x7b-3473-v77-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/config.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/tokenizer_config.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/tokenizer.model
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/special_tokens_map.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/tokenizer.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/flywheel_model.3.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/flywheel_model.3.safetensors
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/flywheel_model.2.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/flywheel_model.2.safetensors
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/flywheel_model.1.safetensors
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-3473-v77/flywheel_model.0.safetensors
mistralai-mixtral-8x7b-3473-v77-mkmlizer: loading reward model from ChaiML/gpt2_medium_pairwise_60m_step_937500
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argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mixtral-8x7b-3473-v77-mkmlizer: warnings.warn(
mistralai-mixtral-8x7b-3473-v77-mkmlizer: /opt/conda/lib/python3.10/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
mistralai-mixtral-8x7b-3473-v77-mkmlizer: warnings.warn(
mistralai-mixtral-8x7b-3473-v77-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:769: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mixtral-8x7b-3473-v77-mkmlizer: warnings.warn(
mistralai-mixtral-8x7b-3473-v77-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.
mistralai-mixtral-8x7b-3473-v77-mkmlizer: warnings.warn(
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Saving duration: 0.498s
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Processed model ChaiML/gpt2_medium_pairwise_60m_step_937500 in 7.183s
mistralai-mixtral-8x7b-3473-v77-mkmlizer: creating bucket guanaco-reward-models
mistralai-mixtral-8x7b-3473-v77-mkmlizer: Bucket 's3://guanaco-reward-models/' created
mistralai-mixtral-8x7b-3473-v77-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/config.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/special_tokens_map.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/tokenizer_config.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/merges.txt
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/vocab.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/tokenizer.json
mistralai-mixtral-8x7b-3473-v77-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/mistralai-mixtral-8x7b-3473-v77_reward/reward.tensors
Job mistralai-mixtral-8x7b-3473-v77-mkmlizer completed after 406.17s with status: succeeded
Stopping job with name mistralai-mixtral-8x7b-3473-v77-mkmlizer
Pipeline stage MKMLizer completed in 407.02s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.13s
Running pipeline stage ISVCDeployer
Creating inference service mistralai-mixtral-8x7b-3473-v77
Waiting for inference service mistralai-mixtral-8x7b-3473-v77 to be ready
Inference service mistralai-mixtral-8x7b-3473-v77 ready after 70.59380102157593s
Pipeline stage ISVCDeployer completed in 77.55s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.5285160541534424s
Received healthy response to inference request in 1.639683723449707s
Received healthy response to inference request in 1.4863991737365723s
Received healthy response to inference request in 1.5800707340240479s
Received healthy response to inference request in 1.4170997142791748s
5 requests
0 failed requests
5th percentile: 1.4309596061706542
10th percentile: 1.4448194980621338
20th percentile: 1.4725392818450929
30th percentile: 1.5051334857940675
40th percentile: 1.5426021099090577
50th percentile: 1.5800707340240479
60th percentile: 1.6039159297943115
70th percentile: 1.6277611255645752
80th percentile: 1.8174501895904542
90th percentile: 2.1729831218719484
95th percentile: 2.350749588012695
99th percentile: 2.492962760925293
mean time: 1.730353879928589
Pipeline stage StressChecker completed in 9.48s
mistralai-mixtral-8x7b-_3473_v77 status is now deployed due to DeploymentManager action
mistralai-mixtral-8x7b-_3473_v77 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of mistralai-mixtral-8x7b-_3473_v77
Running pipeline stage ISVCDeleter
Checking if service mistralai-mixtral-8x7b-3473-v77 is running
Skipping teardown as no inference service was found
Pipeline stage ISVCDeleter completed in 4.84s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key mistralai-mixtral-8x7b-3473-v77/config.json from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/flywheel_model.1.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/flywheel_model.2.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/flywheel_model.3.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/tokenizer.json from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/tokenizer.model from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-3473-v77/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/config.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/merges.txt from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/reward.tensors from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-3473-v77_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 9.58s
mistralai-mixtral-8x7b-_3473_v77 status is now torndown due to DeploymentManager action