developer_uid: richhx
submission_id: chaiml-ca18-c13f-linear-w01_v38
model_name: chaiml-ca18-c13f-linear-w01_v38
model_group: ChaiML/ca18-c13f-linear-
status: torndown
timestamp: 2026-01-16T23:38:38+00:00
num_battles: 11646
num_wins: 5661
celo_rating: 1287.0
family_friendly_score: 0.5247999999999999
family_friendly_standard_error: 0.007062364476575816
submission_type: basic
model_repo: ChaiML/ca18-c13f-linear-w01
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 7
max_input_tokens: 1280
max_output_tokens: 60
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.9529224042521723, 'latency_mean': 1.0493354022502899, 'latency_p50': 1.0439486503601074, 'latency_p90': 1.1763153553009034}, {'batch_size': 5, 'throughput': 2.3946840109610914, 'latency_mean': 2.0852247631549834, 'latency_p50': 2.0895296335220337, 'latency_p90': 2.3507989168167116}, {'batch_size': 10, 'throughput': 2.9250236528625435, 'latency_mean': 3.3978541076183317, 'latency_p50': 3.419689655303955, 'latency_p90': 3.9444843530654907}, {'batch_size': 15, 'throughput': 3.103824790142002, 'latency_mean': 4.779617838859558, 'latency_p50': 4.821874618530273, 'latency_p90': 5.465443968772888}, {'batch_size': 20, 'throughput': 3.1781133604896343, 'latency_mean': 6.197131060361862, 'latency_p50': 6.203712344169617, 'latency_p90': 7.214594101905822}]
gpu_counts: {'NVIDIA L40S': 1}
display_name: chaiml-ca18-c13f-linear-w01_v38
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: ChaiML/ca18-c13f-linear-w01
model_size: 13B
ranking_group: single
throughput_3p7s: 3.0
us_pacific_date: 2026-01-13
win_ratio: 0.4860896445131376
generation_params: {'temperature': 1.0, 'top_p': 0.95, 'min_p': 0.05, 'top_k': 60, 'presence_penalty': 0.15, 'frequency_penalty': 0.15, 'stopping_words': ['</s>', 'You:', '\n', '###'], 'max_input_tokens': 1280, 'best_of': 7, 'max_output_tokens': 60}
formatter: {'memory_template': '', 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': True}
Resubmit model
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chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: Downloaded to shared memory in 28.619s
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: Checking if ChaiML/2fe5-c13f-linear-w01 already exists in ChaiML
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmph5nvjogg, device:0
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
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chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: __import__('pkg_resources').declare_namespace(__name__)
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
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chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
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chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ Version: 0.30.6+torch280 ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ █████ █████ █████ ░░████ █████ ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ ░░░░░ ░░░░░ ░░░░░ ░░░░ ░░░░░ ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ https://mk1.ai ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ Version: 0.30.6+torch280 ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ belonging to: ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ https://mk1.ai ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ Chai Research Corp. ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ belonging to: ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ║ ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ Chai Research Corp. ║
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ║ ║
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: Downloaded to shared memory in 49.218s
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: Checking if ChaiML/2a6f-69d4-linear-w01 already exists in ChaiML
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpwlstf01d, device:0
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: Downloaded to shared memory in 45.605s
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: Checking if ChaiML/ssnew-v5-dpo-lr5e6b01-lora already exists in ChaiML
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpv80yc7l_, device:0
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: The tokenizer you are loading from '/tmp/tmph5nvjogg' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: quantized model in 162.337s
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: Processed model ChaiML/2fe5-c13f-linear-w01 in 190.956s
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: creating bucket guanaco-mkml-models
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/chat_template.jinja s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia/chat_template.jinja
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia/special_tokens_map.json
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia/config.json
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia/tokenizer_config.json
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia/tokenizer.json
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: bash: no job control in this shell
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: __import__('pkg_resources').declare_namespace(__name__)
chaiml-2fe5-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-2fe5-c13f-linear-w01-v38/nvidia/flywheel_model.0.safetensors
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chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ ║
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ Version: 0.30.6+torch280 ║
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
Job chaiml-2fe5-c13f-linear-w01-v38-mkmlizer completed after 294.38s with status: succeeded
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: bash: no job control in this shell
Stopping job with name chaiml-2fe5-c13f-linear-w01-v38-mkmlizer
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ https://mk1.ai ║
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ ║
Pipeline stage MKMLizer completed in 297.71s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ The license key for the current software has been verified as ║
run pipeline stage %s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ belonging to: ║
Running pipeline stage MKMLTemplater
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ ║
Pipeline stage MKMLTemplater completed in 1.00s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ Chai Research Corp. ║
run pipeline stage %s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
Running pipeline stage MKMLDeployer
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
Creating inference service chaiml-2fe5-c13f-linear-w01-v38
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ║ ║
Waiting for inference service chaiml-2fe5-c13f-linear-w01-v38 to be ready
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: Downloaded to shared memory in 45.925s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: Checking if ChaiML/7b07-69d4-linear-w01 already exists in ChaiML
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: Downloaded to shared memory in 23.899s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpfkv5l4a_, device:0
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: Checking if ChaiML/ca18-c13f-linear-w01 already exists in ChaiML
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpr07yf5pi, device:0
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: bash: no job control in this shell
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: bash: no job control in this shell
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: __import__('pkg_resources').declare_namespace(__name__)
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chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ ░███ ░░░ ░███ ░███░░███ ░███ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: bash: no job control in this shell
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chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ █████ █████ █████ ░░████ █████ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: __import__('pkg_resources').declare_namespace(__name__)
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ ░░░░░ ░░░░░ ░░░░░ ░░░░ ░░░░░ ║
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chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ Version: 0.30.6+torch280 ║
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: Downloaded to shared memory in 24.021s
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ██████ ██████ █████ ████ ████ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: Checking if ChaiML/4d70-fd43-linear-w01 already exists in ChaiML
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ░░██████ ██████ ░░███ ███░ ░░███ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpuh2m92ld, device:0
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ░███░█████░███ ░███ ███ ░███ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ https://mk1.ai ║
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ░███░░███ ░███ ░███████ ░███ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ░███ ░░░ ░███ ░███░░███ ░███ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ░███ ░███ ░███ ░░███ ░███ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ belonging to: ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ █████ █████ █████ ░░████ █████ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ░░░░░ ░░░░░ ░░░░░ ░░░░ ░░░░░ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ Chai Research Corp. ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ Version: 0.30.6+torch280 ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ https://mk1.ai ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ belonging to: ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ Chai Research Corp. ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ║ ║
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: Downloaded to shared memory in 44.352s
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: Checking if ChaiML/02f4-69d4-linear-w01 already exists in ChaiML
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpaxwec01f, device:0
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: Downloaded to shared memory in 47.960s
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: Checking if ChaiML/csfs-v3-3-dpo-lr5e6b01-lora already exists in ChaiML
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpjuyoa30u, device:0
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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chaiml-ca18-c13f-linear-w01-v38-mkmlizer: The tokenizer you are loading from '/tmp/tmpr07yf5pi' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: quantized model in 141.785s
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: Processed model ChaiML/ca18-c13f-linear-w01 in 165.684s
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: creating bucket guanaco-mkml-models
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia/config.json
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/chat_template.jinja s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia/chat_template.jinja
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia/special_tokens_map.json
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia/tokenizer_config.json
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia/tokenizer.json
Inference service chaiml-2fe5-c13f-linear-w01-v38 ready after 182.57392191886902s
Pipeline stage MKMLDeployer completed in 187.85s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.8155004978179932s
Received healthy response to inference request in 1.5893335342407227s
Received healthy response to inference request in 1.1920185089111328s
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: The tokenizer you are loading from '/tmp/tmpv80yc7l_' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: quantized model in 277.543s
Received healthy response to inference request in 1.3988900184631348s
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: Processed model ChaiML/ssnew-v5-dpo-lr5e6b01-lora in 323.148s
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: creating bucket guanaco-mkml-models
Received healthy response to inference request in 1.5542151927947998s
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
5 requests
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia
0 failed requests
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia/config.json
5th percentile: 1.2333928108215333
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia/special_tokens_map.json
10th percentile: 1.2747671127319335
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia/tokenizer_config.json
20th percentile: 1.3575157165527343
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia/tokenizer.json
30th percentile: 1.4299550533294678
40th percentile: 1.4920851230621337
50th percentile: 1.5542151927947998
60th percentile: 1.568262529373169
70th percentile: 1.582309865951538
80th percentile: 1.634566926956177
90th percentile: 1.725033712387085
95th percentile: 1.770267105102539
99th percentile: 1.8064538192749022
mean time: 1.5099915504455566
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Pipeline stage StressChecker completed in 28.19s
chaiml-ca18-c13f-linear-w01-v38-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-ca18-c13f-linear-w01-v38/nvidia/flywheel_model.0.safetensors
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 5.03s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: The tokenizer you are loading from '/tmp/tmpuh2m92ld' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
run_pipeline:run_in_cloud %s
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia/flywheel_model.1.safetensors
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: quantized model in 141.669s
Job chaiml-ca18-c13f-linear-w01-v38-mkmlizer completed after 530.13s with status: succeeded
starting trigger_guanaco_pipeline args=%s
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: Processed model ChaiML/4d70-fd43-linear-w01 in 165.690s
Stopping job with name chaiml-ca18-c13f-linear-w01-v38-mkmlizer
triggered trigger_guanaco_pipeline args=%s
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: creating bucket guanaco-mkml-models
Pipeline stage MKMLizer completed in 534.35s
Pipeline stage TriggerMKMLProfilingPipeline completed in 5.87s
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
run pipeline stage %s
Shutdown handler de-registered
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: The tokenizer you are loading from '/tmp/tmpwlstf01d' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
Running pipeline stage MKMLTemplater
chaiml-2fe5-c13f-linear-w01_v38 status is now deployed due to DeploymentManager action
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: cp /dev/shm/model_cache/chat_template.jinja s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia/chat_template.jinja
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: quantized model in 312.878s
Pipeline stage MKMLTemplater completed in 1.62s
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia/config.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: Processed model ChaiML/2a6f-69d4-linear-w01 in 362.096s
run pipeline stage %s
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia/special_tokens_map.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: creating bucket guanaco-mkml-models
Running pipeline stage MKMLDeployer
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia/tokenizer_config.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
Creating inference service chaiml-ca18-c13f-linear-w01-v38
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia/tokenizer.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia
Waiting for inference service chaiml-ca18-c13f-linear-w01-v38 to be ready
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/special_tokens_map.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/chat_template.jinja s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/chat_template.jinja
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/tokenizer_config.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/config.json
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/tokenizer.json
chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-ssnew-v5-dpo-lr-24415-v22/nvidia/flywheel_model.0.safetensors
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/flywheel_model.1.safetensors
Job chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer completed after 454.97s with status: succeeded
Stopping job with name chaiml-ssnew-v5-dpo-lr-24415-v22-mkmlizer
Pipeline stage MKMLizer completed in 459.15s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 1.06s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-ssnew-v5-dpo-lr-24415-v22
Waiting for inference service chaiml-ssnew-v5-dpo-lr-24415-v22 to be ready
chaiml-4d70-fd43-linear-w01-v29-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-4d70-fd43-linear-w01-v29/nvidia/flywheel_model.0.safetensors
Job chaiml-4d70-fd43-linear-w01-v29-mkmlizer completed after 470.87s with status: succeeded
Stopping job with name chaiml-4d70-fd43-linear-w01-v29-mkmlizer
Pipeline stage MKMLizer completed in 474.72s
run pipeline stage %s
Running pipeline stage MKMLTemplater
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Pipeline stage MKMLTemplater completed in 1.12s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: The tokenizer you are loading from '/tmp/tmpfkv5l4a_' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
run pipeline stage %s
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: quantized model in 276.228s
Running pipeline stage MKMLDeployer
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: Processed model ChaiML/7b07-69d4-linear-w01 in 322.153s
Creating inference service chaiml-4d70-fd43-linear-w01-v29
Waiting for inference service chaiml-4d70-fd43-linear-w01-v29 to be ready
chaiml-2a6f-69d4-linear-w01-v24-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-2a6f-69d4-linear-w01-v24/nvidia/flywheel_model.0.safetensors
Job chaiml-2a6f-69d4-linear-w01-v24-mkmlizer completed after 485.29s with status: succeeded
Stopping job with name chaiml-2a6f-69d4-linear-w01-v24-mkmlizer
Pipeline stage MKMLizer completed in 489.35s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 1.10s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-2a6f-69d4-linear-w01-v24
Waiting for inference service chaiml-2a6f-69d4-linear-w01-v24 to be ready
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-7b07-69d4-linear-w01-v33/nvidia/flywheel_model.1.safetensors
chaiml-7b07-69d4-linear-w01-v33-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-7b07-69d4-linear-w01-v33/nvidia/flywheel_model.0.safetensors
Tearing down inference service chaiml-4d70-fd43-linear-w01-v29
%s, retrying in %s seconds...
Job chaiml-7b07-69d4-linear-w01-v33-mkmlizer completed after 682.94s with status: succeeded
Creating inference service chaiml-4d70-fd43-linear-w01-v29
Stopping job with name chaiml-7b07-69d4-linear-w01-v33-mkmlizer
Waiting for inference service chaiml-4d70-fd43-linear-w01-v29 to be ready
Pipeline stage MKMLizer completed in 686.69s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 1.58s
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run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-7b07-69d4-linear-w01-v33
Waiting for inference service chaiml-7b07-69d4-linear-w01-v33 to be ready
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: The tokenizer you are loading from '/tmp/tmpaxwec01f' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: quantized model in 276.703s
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: Processed model ChaiML/02f4-69d4-linear-w01 in 321.055s
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: creating bucket guanaco-mkml-models
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia/config.json
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia/special_tokens_map.json
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia/tokenizer_config.json
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chaiml-02f4-69d4-linear-w01-v51-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia/tokenizer.json
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: The tokenizer you are loading from '/tmp/tmpjuyoa30u' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: quantized model in 276.995s
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: Processed model ChaiML/csfs-v3-3-dpo-lr5e6b01-lora in 324.955s
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: creating bucket guanaco-mkml-models
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-csfs-v3-3-dpo-l-86358-v21/nvidia
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-csfs-v3-3-dpo-l-86358-v21/nvidia/config.json
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-csfs-v3-3-dpo-l-86358-v21/nvidia/special_tokens_map.json
Inference service chaiml-ca18-c13f-linear-w01-v38 ready after 182.76718926429749s
Pipeline stage MKMLDeployer completed in 187.54s
run pipeline stage %s
Running pipeline stage StressChecker
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia/flywheel_model.1.safetensors
Received healthy response to inference request in 1.7081851959228516s
Received healthy response to inference request in 1.604926347732544s
Received healthy response to inference request in 1.5645837783813477s
Received healthy response to inference request in 1.194702386856079s
Received healthy response to inference request in 1.2659308910369873s
5 requests
0 failed requests
5th percentile: 1.2089480876922607
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-csfs-v3-3-dpo-l-86358-v21/nvidia/flywheel_model.1.safetensors
10th percentile: 1.2231937885284423
20th percentile: 1.2516851902008057
30th percentile: 1.3256614685058594
40th percentile: 1.4451226234436034
50th percentile: 1.5645837783813477
60th percentile: 1.580720806121826
70th percentile: 1.5968578338623047
80th percentile: 1.6255781173706054
90th percentile: 1.6668816566467286
95th percentile: 1.68753342628479
99th percentile: 1.7040548419952393
Inference service chaiml-ssnew-v5-dpo-lr-24415-v22 ready after 172.65151381492615s
mean time: 1.467665719985962
Pipeline stage MKMLDeployer completed in 177.47s
Pipeline stage StressChecker completed in 40.48s
run pipeline stage %s
run pipeline stage %s
Running pipeline stage StressChecker
chaiml-02f4-69d4-linear-w01-v51-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-02f4-69d4-linear-w01-v51/nvidia/flywheel_model.0.safetensors
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
Inference service chaiml-4d70-fd43-linear-w01-v29 ready after 91.36040925979614s
Job chaiml-02f4-69d4-linear-w01-v51-mkmlizer completed after 630.86s with status: succeeded
run_pipeline:run_in_cloud %s
Pipeline stage MKMLDeployer completed in 173.34s
Stopping job with name chaiml-02f4-69d4-linear-w01-v51-mkmlizer
Received healthy response to inference request in 3.075303077697754s
starting trigger_guanaco_pipeline args=%s
run pipeline stage %s
Pipeline stage MKMLizer completed in 786.54s
Running pipeline stage StressChecker
run pipeline stage %s
triggered trigger_guanaco_pipeline args=%s
Received healthy response to inference request in 2.2296791076660156s
chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-csfs-v3-3-dpo-l-86358-v21/nvidia/flywheel_model.0.safetensors
Running pipeline stage MKMLTemplater
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 10.27s
Received healthy response to inference request in 1.96047043800354s
Pipeline stage MKMLTemplater completed in 2.33s
run pipeline stage %s
Received healthy response to inference request in 2.600219488143921s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
Received healthy response to inference request in 2.653022050857544s
Running pipeline stage MKMLDeployer
run_pipeline:run_in_cloud %s
Received healthy response to inference request in 2.5749146938323975s
Creating inference service chaiml-02f4-69d4-linear-w01-v51
starting trigger_guanaco_pipeline args=%s
Received healthy response to inference request in 2.337405204772949s
Job chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer completed after 662.29s with status: succeeded
Waiting for inference service chaiml-02f4-69d4-linear-w01-v51 to be ready
triggered trigger_guanaco_pipeline args=%s
Received healthy response to inference request in 1.817976713180542s
Stopping job with name chaiml-csfs-v3-3-dpo-l-86358-v21-mkmlizer
Inference service chaiml-2a6f-69d4-linear-w01-v24 ready after 172.6989951133728s
Received healthy response to inference request in 2.1879191398620605s
Pipeline stage TriggerMKMLProfilingPipeline completed in 9.80s
5 requests
Pipeline stage MKMLizer completed in 669.55s
Pipeline stage MKMLDeployer completed in 179.82s
Shutdown handler de-registered
0 failed requests
run pipeline stage %s
Received healthy response to inference request in 2.1102688312530518s
0 failed requests
run pipeline stage %s
Received healthy response to inference request in 2.1102688312530518s
run pipeline stage %s
chaiml-ca18-c13f-linear-w01_v38 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Generating Leaderboard row for %s
Generated Leaderboard row for %s
Pipeline stage OfflineFamilyFriendlyScorer completed in 1877.79s
Shutdown handler de-registered
chaiml-ca18-c13f-linear-w01_v38 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of chaiml-ca18-c13f-linear-w01_v38
Shutdown handler not registered because Python interpreter is not running in the main thread
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Pipeline stage MKMLDeleter completed in 106.45s
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Pipeline stage MKMLModelDeleter completed in 253.21s
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Falling back to EndpointApi.from_submission implementation
Falling back to EndpointApi.from_submission implementation
Falling back to EndpointApi.from_submission implementation
Falling back to EndpointApi.from_submission implementation
Falling back to EndpointApi.from_submission implementation
Falling back to EndpointApi.from_submission implementation
Falling back to EndpointApi.from_submission implementation