submission_id: cgato-smallsmorts-l3-8b-v0-1_v3
developer_uid: c.gato
status: inactive
model_repo: cgato/SmallSmorts-L3-8b-v0.1
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.9, 'top_p': 0.9, 'min_p': 0.0, 'top_k': 200, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
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': True}
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': True}
timestamp: 2024-06-16T15:29:39+00:00
model_name: cgato-smallsmorts-l3-8b-v0-1_v2
model_eval_status: success
model_group: cgato/SmallSmorts-L3-8b-
num_battles: 30212
num_wins: 16368
celo_rating: 1197.44
propriety_score: 0.7046421421421422
propriety_total_count: 15984.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030294016.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: cgato-smallsmorts-l3-8b-v0-1_v2
ineligible_reason: None
language_model: cgato/SmallSmorts-L3-8b-v0.1
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-16
win_ratio: 0.5417714815305177
Resubmit model
Running pipeline stage MKMLizer
Starting job with name cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer
Waiting for job on cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer to finish
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ _____ __ __ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ /___/ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Version: 0.8.14 ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ https://mk1.ai ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ The license key for the current software has been verified as ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ belonging to: ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Chai Research Corp. ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cgato-smallsmorts-l3-8b-v0-1-v3-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.
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: warnings.warn(warning_message, FutureWarning)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Traceback (most recent call last):
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/file_download.py", line 509, in http_get
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: hf_transfer.download(
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Exception: Error while downloading: reqwest::Error { kind: Request, url: Url { scheme: "https", cannot_be_a_base: false, username: "", password: None, host: Some(Domain("cdn-lfs-us-1.huggingface.co")), port: None, path: "/repos/51/46/e1a4b56cbdc86e1f4d7d0/49e88a8c193716e4db4e2f2573e14075718c08bd313ea01cea03cfb22c7b0a1c", query: Some("response-content-disposition=inline%3B+filename*%3DUTF-8%27%27model-00001-of-00004.safetensors%3B+filename%3D%22model-00001-of-00004.safetensors%22%3B&Expires=1718810989&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcxODgxMDk4OX19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy11cy0xLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzUxLzQ2LzUxNDYzMTIxNWZjMjA4OGZjMDgzMDRjYmNiMjIxODYwY2I2ODI3NjA3NjllMWE0YjU2Y2JkYzg2ZTFmNGQ3ZDAvNDllODhhOGMxOTM3MTZlNGRiNGUyZjI1NzNlMTQwNzU3MThjMDhiZDMxM2VhMDFjZWEwM2NmYjIyYzdiMGExYz9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoifV19&Signature=hQOelKyC9aQ9O1PvuHg9CgBmOWB6lR08Ut4IXMHZpvbeYr0MNQZrNo03SAo8Ie7l9L6nGyvxEN4N6xQYMU1RGT93Sf4nvBrZd9rjxMyG4%7EDOxiHPtdMjUmSIle9MMJBdE0zsRaoYnZxvGVDX7lZ0bYyZVFbSvEWaI0cAa4O6TlR7iotdihPrSt903-lW7ozzErtyw%7ElW6owiLTfTkkC3f6inB52LDRbuEGJGiMuU56cmQNKmebTAL9c0xpIPZM0scKRg8BSVsq53aCbXtnCeHnTjMyiEU6lN0vKzDwZ4c%7E9g7iyUYcYGJ4jlweAPS1rCtQU69H-P6qf95ggFeDKjqw__&Key-Pair-Id=K2FPYV99P2N66Q"), fragment: None }, source: hyper::Error(Connect, ConnectError("dns error", Custom { kind: Uncategorized, error: "failed to lookup address information: Temporary failure in name resolution" })) }
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: The above exception was the direct cause of the following exception:
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Traceback (most recent call last):
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/code/uploading/mkmlize.py", line 151, in <module>
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cli()
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1128, in __call__
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return self.main(*args, **kwargs)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1053, in main
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: rv = self.invoke(ctx)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1659, in invoke
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return _process_result(sub_ctx.command.invoke(sub_ctx))
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1395, in invoke
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return ctx.invoke(self.callback, **ctx.params)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 754, in invoke
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return __callback(*args, **kwargs)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/code/uploading/mkmlize.py", line 38, in quantize
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: temp_folder = download_to_shared_memory(repo_id, revision, hf_auth_token)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/code/uploading/mkmlize.py", line 65, in download_to_shared_memory
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: snapshot_download(
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 119, in _inner_fn
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return fn(*args, **kwargs)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/_snapshot_download.py", line 314, in snapshot_download
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: _inner_hf_hub_download(file)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/_snapshot_download.py", line 290, in _inner_hf_hub_download
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return hf_hub_download(
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 119, in _inner_fn
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return fn(*args, **kwargs)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/file_download.py", line 1492, in hf_hub_download
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: http_get(
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: File "/opt/conda/lib/python3.10/site-packages/huggingface_hub/file_download.py", line 520, in http_get
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: raise RuntimeError(
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: RuntimeError: An error occurred while downloading using `hf_transfer`. Consider disabling HF_HUB_ENABLE_HF_TRANSFER for better error handling.
Job cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer completed after 22.0s with status: failed
Stopping job with name cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer
%s, retrying in %s seconds...
Starting job with name cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer
Waiting for job on cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer to finish
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ _____ __ __ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ /___/ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Version: 0.8.14 ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ https://mk1.ai ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ The license key for the current software has been verified as ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ belonging to: ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Chai Research Corp. ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ║ ║
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cgato-smallsmorts-l3-8b-v0-1-v3-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.
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: warnings.warn(warning_message, FutureWarning)
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Downloaded to shared memory in 44.479s
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: quantizing model to /dev/shm/model_cache
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
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cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: quantized model in 25.122s
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Processed model cgato/SmallSmorts-L3-8b-v0.1 in 72.180s
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: creating bucket guanaco-mkml-models
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cgato-smallsmorts-l3-8b-v0-1-v3
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cgato-smallsmorts-l3-8b-v0-1-v3/special_tokens_map.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cgato-smallsmorts-l3-8b-v0-1-v3/config.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cgato-smallsmorts-l3-8b-v0-1-v3/tokenizer_config.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cgato-smallsmorts-l3-8b-v0-1-v3/tokenizer.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cgato-smallsmorts-l3-8b-v0-1-v3/flywheel_model.0.safetensors
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
cgato-smallsmorts-l3-8b-v0-1-v3-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.
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: warnings.warn(
cgato-smallsmorts-l3-8b-v0-1-v3-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.
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: warnings.warn(
cgato-smallsmorts-l3-8b-v0-1-v3-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.
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: warnings.warn(
cgato-smallsmorts-l3-8b-v0-1-v3-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()
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: return self.fget.__get__(instance, owner)()
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Saving duration: 0.420s
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 12.695s
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: creating bucket guanaco-reward-models
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: Bucket 's3://guanaco-reward-models/' created
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/special_tokens_map.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/merges.txt
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/tokenizer_config.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/config.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/vocab.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/tokenizer.json
cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/cgato-smallsmorts-l3-8b-v0-1-v3_reward/reward.tensors
Job cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer completed after 124.34s with status: succeeded
Stopping job with name cgato-smallsmorts-l3-8b-v0-1-v3-mkmlizer
Pipeline stage MKMLizer completed in 150.72s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service cgato-smallsmorts-l3-8b-v0-1-v3
Waiting for inference service cgato-smallsmorts-l3-8b-v0-1-v3 to be ready
Inference service cgato-smallsmorts-l3-8b-v0-1-v3 ready after 40.21132707595825s
Pipeline stage ISVCDeployer completed in 47.62s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.0421690940856934s
Received healthy response to inference request in 1.2598786354064941s
Received healthy response to inference request in 1.2703988552093506s
Received healthy response to inference request in 1.2868356704711914s
Received healthy response to inference request in 1.2828679084777832s
5 requests
0 failed requests
5th percentile: 1.2619826793670654
10th percentile: 1.2640867233276367
20th percentile: 1.2682948112487793
30th percentile: 1.272892665863037
40th percentile: 1.2778802871704102
50th percentile: 1.2828679084777832
60th percentile: 1.2844550132751464
70th percentile: 1.2860421180725097
80th percentile: 1.437902355194092
90th percentile: 1.7400357246398928
95th percentile: 1.8911024093627928
99th percentile: 2.0119557571411133
mean time: 1.4284300327301025
Pipeline stage StressChecker completed in 7.97s
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 0.06s
M-Eval Dataset for topic stay_in_character is loaded
cgato-smallsmorts-l3-8b-v0-1_v3 status is now deployed due to DeploymentManager action
cgato-smallsmorts-l3-8b-v0-1_v3 status is now inactive due to auto deactivation removed underperforming models

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