junhua024-chai-1-full_94469

developer_uid: junhua024
submission_id: junhua024-chai-1-full_94469_v110
model_name: junhua024-chai-1-full_94469_v110
model_group: junhua024/chai-1-full-06
status: torndown
timestamp: 2025-07-16T09:55:37+00:00
num_battles: 8167
num_wins: 3779
celo_rating: 1268.75
family_friendly_score: 0.556
family_friendly_standard_error: 0.007026578114559035
submission_type: basic
model_repo: junhua024/chai-1-full-066126
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.5960613671529615, 'latency_mean': 1.6775048804283141, 'latency_p50': 1.6789742708206177, 'latency_p90': 1.8411290645599365}, {'batch_size': 3, 'throughput': 1.089906355245874, 'latency_mean': 2.7387473618984224, 'latency_p50': 2.7387274503707886, 'latency_p90': 3.015627861022949}, {'batch_size': 5, 'throughput': 1.315040481256387, 'latency_mean': 3.785900399684906, 'latency_p50': 3.7942906618118286, 'latency_p90': 4.194875764846802}, {'batch_size': 6, 'throughput': 1.37219325886912, 'latency_mean': 4.348739470243454, 'latency_p50': 4.348208427429199, 'latency_p90': 4.862136745452881}, {'batch_size': 8, 'throughput': 1.4454494387830708, 'latency_mean': 5.482388099431992, 'latency_p50': 5.462806344032288, 'latency_p90': 6.157719111442566}, {'batch_size': 10, 'throughput': 1.4863921843154462, 'latency_mean': 6.683311331272125, 'latency_p50': 6.723552227020264, 'latency_p90': 7.524580645561218}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-1-full_94469_v110
is_internal_developer: False
language_model: junhua024/chai-1-full-066126
model_size: 13B
ranking_group: single
throughput_3p7s: 1.31
us_pacific_date: 2025-07-16
win_ratio: 0.46271580751806046
generation_params: {'temperature': 1.0, 'top_p': 0.885, 'min_p': 0.0, 'top_k': 10, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, '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}
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name junhua024-chai-1-full-94469-v110-mkmlizer
Waiting for job on junhua024-chai-1-full-94469-v110-mkmlizer to finish
junhua024-chai-1-full-94469-v110-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
junhua024-chai-1-full-94469-v110-mkmlizer: ║                                                                     ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║                                                                     ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║                                                                     ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║                                                                     ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-1-full-94469-v110-mkmlizer: ║                                                                     ║
junhua024-chai-1-full-94469-v110-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-1-full-94469-v110-mkmlizer: Downloaded to shared memory in 73.667s
junhua024-chai-1-full-94469-v110-mkmlizer: Checking if junhua024/chai-1-full-066126 already exists in ChaiML
junhua024-chai-1-full-94469-v110-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpa7jpq79i, device:0
junhua024-chai-1-full-94469-v110-mkmlizer: Saving flywheel model at /dev/shm/model_cache
junhua024-chai-1-full-94469-v110-mkmlizer: quantized model in 31.711s
junhua024-chai-1-full-94469-v110-mkmlizer: Processed model junhua024/chai-1-full-066126 in 105.463s
junhua024-chai-1-full-94469-v110-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-1-full-94469-v110-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-1-full-94469-v110-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-1-full-94469-v110/nvidia
junhua024-chai-1-full-94469-v110-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-1-full-94469-v110/nvidia/config.json
junhua024-chai-1-full-94469-v110-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-1-full-94469-v110/nvidia/special_tokens_map.json
junhua024-chai-1-full-94469-v110-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-1-full-94469-v110/nvidia/tokenizer_config.json
junhua024-chai-1-full-94469-v110-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-1-full-94469-v110/nvidia/tokenizer.json
junhua024-chai-1-full-94469-v110-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-1-full-94469-v110/nvidia/flywheel_model.0.safetensors
junhua024-chai-1-full-94469-v110-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|          | 2/363 [00:00<00:25, 13.90it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:20, 17.27it/s]
Loading 0:   3%|▎         | 12/363 [00:00<00:12, 28.15it/s]
Loading 0:   5%|▍         | 17/363 [00:00<00:11, 29.67it/s]
Loading 0:   6%|▋         | 23/363 [00:00<00:10, 31.00it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:07, 41.90it/s]
Loading 0:  10%|▉         | 36/363 [00:01<00:10, 31.35it/s]
Loading 0:  11%|█▏        | 41/363 [00:01<00:09, 32.48it/s]
Loading 0:  14%|█▍        | 50/363 [00:01<00:07, 39.64it/s]
Loading 0:  15%|█▌        | 55/363 [00:01<00:09, 33.97it/s]
Loading 0:  16%|█▋        | 59/363 [00:01<00:09, 33.37it/s]
Loading 0:  18%|█▊        | 65/363 [00:01<00:08, 33.94it/s]
Loading 0:  19%|█▉        | 69/363 [00:02<00:08, 32.94it/s]
Loading 0:  20%|██        | 74/363 [00:02<00:07, 36.43it/s]
Loading 0:  21%|██▏       | 78/363 [00:02<00:07, 37.11it/s]
Loading 0:  23%|██▎       | 82/363 [00:02<00:08, 32.16it/s]
Loading 0:  24%|██▎       | 86/363 [00:02<00:08, 33.92it/s]
Loading 0:  25%|██▌       | 91/363 [00:02<00:07, 34.58it/s]
Loading 0:  27%|██▋       | 97/363 [00:02<00:07, 35.80it/s]
Loading 0:  28%|██▊       | 101/363 [00:03<00:07, 35.63it/s]
Loading 0:  29%|██▉       | 105/363 [00:03<00:07, 33.40it/s]
Loading 0:  31%|███       | 113/363 [00:03<00:06, 39.21it/s]
Loading 0:  32%|███▏      | 117/363 [00:03<00:08, 30.22it/s]
Loading 0:  34%|███▎      | 122/363 [00:03<00:07, 31.89it/s]
Loading 0:  35%|███▌      | 128/363 [00:03<00:07, 33.57it/s]
Loading 0:  36%|███▋      | 132/363 [00:03<00:07, 32.73it/s]
Loading 0:  38%|███▊      | 137/363 [00:04<00:06, 36.44it/s]
Loading 0:  39%|███▉      | 141/363 [00:04<00:06, 36.60it/s]
Loading 0:  40%|███▉      | 145/363 [00:04<00:06, 31.98it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:06, 31.10it/s]
Loading 0:  43%|████▎     | 155/363 [00:04<00:05, 37.81it/s]
Loading 0:  44%|████▍     | 160/363 [00:04<00:05, 36.20it/s]
Loading 0:  45%|████▌     | 164/363 [00:04<00:05, 35.22it/s]
Loading 0:  46%|████▋     | 168/363 [00:04<00:05, 33.07it/s]
Loading 0:  48%|████▊     | 176/363 [00:05<00:04, 39.33it/s]
Loading 0:  50%|████▉     | 180/363 [00:05<00:05, 31.77it/s]
Loading 0:  51%|█████     | 185/363 [00:05<00:05, 33.55it/s]
Loading 0:  53%|█████▎    | 191/363 [00:05<00:04, 34.91it/s]
Loading 0:  54%|█████▎    | 195/363 [00:05<00:04, 33.92it/s]
Loading 0:  55%|█████▌    | 201/363 [00:05<00:04, 33.77it/s]
Loading 0:  57%|█████▋    | 206/363 [00:06<00:04, 33.22it/s]
Loading 0:  58%|█████▊    | 212/363 [00:06<00:04, 34.34it/s]
Loading 0:  60%|██████    | 218/363 [00:06<00:03, 39.60it/s]
Loading 0:  61%|██████▏   | 223/363 [00:06<00:03, 37.49it/s]
Loading 0:  63%|██████▎   | 227/363 [00:06<00:03, 36.67it/s]
Loading 0:  64%|██████▎   | 231/363 [00:06<00:03, 33.23it/s]
Loading 0:  66%|██████▌   | 239/363 [00:06<00:03, 38.87it/s]
Loading 0:  67%|██████▋   | 243/363 [00:07<00:03, 31.48it/s]
Loading 0:  68%|██████▊   | 248/363 [00:07<00:03, 33.66it/s]
Loading 0:  70%|██████▉   | 254/363 [00:07<00:03, 34.76it/s]
Loading 0:  71%|███████   | 258/363 [00:07<00:03, 33.29it/s]
Loading 0:  72%|███████▏  | 263/363 [00:07<00:02, 36.73it/s]
Loading 0:  74%|███████▎  | 267/363 [00:07<00:02, 37.39it/s]
Loading 0:  75%|███████▍  | 271/363 [00:07<00:02, 32.09it/s]
Loading 0:  76%|███████▌  | 275/363 [00:08<00:02, 30.76it/s]
Loading 0:  77%|███████▋  | 281/363 [00:08<00:02, 36.05it/s]
Loading 0:  79%|███████▉  | 286/363 [00:08<00:02, 32.85it/s]
Loading 0:  80%|███████▉  | 290/363 [00:08<00:02, 32.42it/s]
Loading 0:  81%|████████  | 294/363 [00:08<00:02, 30.68it/s]
Loading 0:  83%|████████▎ | 301/363 [00:08<00:01, 39.38it/s]
Loading 0:  84%|████████▍ | 306/363 [00:09<00:01, 29.42it/s]
Loading 0:  86%|████████▌ | 311/363 [00:09<00:01, 31.10it/s]
Loading 0:  87%|████████▋ | 317/363 [00:09<00:01, 32.32it/s]
Loading 0:  88%|████████▊ | 321/363 [00:09<00:01, 31.88it/s]
Loading 0:  90%|█████████ | 327/363 [00:09<00:01, 32.30it/s]
Loading 0:  91%|█████████▏| 332/363 [00:09<00:00, 31.88it/s]
Loading 0:  93%|█████████▎| 338/363 [00:10<00:00, 33.19it/s]
Loading 0:  95%|█████████▍| 344/363 [00:10<00:00, 37.66it/s]
Loading 0:  96%|█████████▌| 349/363 [00:10<00:00, 26.02it/s]
Loading 0:  97%|█████████▋| 353/363 [00:10<00:00, 24.01it/s]
Loading 0:  98%|█████████▊| 357/363 [00:10<00:00, 25.60it/s]
                                                            
Job junhua024-chai-1-full-94469-v110-mkmlizer completed after 128.09s with status: succeeded
Stopping job with name junhua024-chai-1-full-94469-v110-mkmlizer
Pipeline stage MKMLizer completed in 128.60s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service junhua024-chai-1-full-94469-v110
Waiting for inference service junhua024-chai-1-full-94469-v110 to be ready
Inference service junhua024-chai-1-full-94469-v110 ready after 270.99983525276184s
Pipeline stage MKMLDeployer completed in 271.61s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.562633991241455s
Received healthy response to inference request in 1.906247615814209s
Received healthy response to inference request in 1.857297420501709s
Received healthy response to inference request in 1.579768419265747s
Received healthy response to inference request in 2.212459087371826s
5 requests
0 failed requests
5th percentile: 1.6352742195129395
10th percentile: 1.690780019760132
20th percentile: 1.8017916202545166
30th percentile: 1.867087459564209
40th percentile: 1.886667537689209
50th percentile: 1.906247615814209
60th percentile: 2.0287322044372558
70th percentile: 2.1512167930603026
80th percentile: 2.282494068145752
90th percentile: 2.4225640296936035
95th percentile: 2.4925990104675293
99th percentile: 2.54862699508667
mean time: 2.023681306838989
Pipeline stage StressChecker completed in 11.90s
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 0.81s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 0.78s
Shutdown handler de-registered
junhua024-chai-1-full_94469_v110 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.15s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service junhua024-chai-1-full-94469-v110-profiler
Waiting for inference service junhua024-chai-1-full-94469-v110-profiler to be ready
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 4311.45s
Shutdown handler de-registered
junhua024-chai-1-full_94469_v110 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-1-full_94469_v110 status is now torndown due to DeploymentManager action
junhua024-chai-1-full_94469_v110 status is now torndown due to DeploymentManager action