developer_uid: Riverise
submission_id: riverise-fliter-0622_v1
model_name: riverise-fliter-0622_v1
model_group: Riverise/fliter_0622
status: torndown
timestamp: 2025-06-25T03:56:38+00:00
num_battles: 6122
num_wins: 2969
celo_rating: 1267.64
family_friendly_score: 0.5642
family_friendly_standard_error: 0.0070125367735221185
submission_type: basic
model_repo: Riverise/fliter_0622
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': 0.5917990112563746, 'latency_mean': 1.6896582329273224, 'latency_p50': 1.7099052667617798, 'latency_p90': 1.8556120634078979}, {'batch_size': 3, 'throughput': 1.0789816100579974, 'latency_mean': 2.7647756481170656, 'latency_p50': 2.740495443344116, 'latency_p90': 3.0396424531936646}, {'batch_size': 5, 'throughput': 1.2925219314080438, 'latency_mean': 3.8565134370326994, 'latency_p50': 3.8650364875793457, 'latency_p90': 4.2733962059021}, {'batch_size': 6, 'throughput': 1.3466887260167915, 'latency_mean': 4.4295201122760774, 'latency_p50': 4.48160982131958, 'latency_p90': 4.9497733354568485}, {'batch_size': 8, 'throughput': 1.41829584989186, 'latency_mean': 5.598666015863419, 'latency_p50': 5.614102125167847, 'latency_p90': 6.330927062034607}, {'batch_size': 10, 'throughput': 1.4520015675218338, 'latency_mean': 6.833617906570435, 'latency_p50': 6.826056599617004, 'latency_p90': 7.829792881011963}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: riverise-fliter-0622_v1
is_internal_developer: False
language_model: Riverise/fliter_0622
model_size: 13B
ranking_group: single
throughput_3p7s: 1.27
us_pacific_date: 2025-06-24
win_ratio: 0.48497223129696176
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, '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': False}
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 riverise-fliter-0622-v1-mkmlizer
Waiting for job on riverise-fliter-0622-v1-mkmlizer to finish
riverise-fliter-0622-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
riverise-fliter-0622-v1-mkmlizer: ║ ║
riverise-fliter-0622-v1-mkmlizer: ║ ██████ ██████ █████ ████ ████ ║
riverise-fliter-0622-v1-mkmlizer: ║ ░░██████ ██████ ░░███ ███░ ░░███ ║
riverise-fliter-0622-v1-mkmlizer: ║ ░███░█████░███ ░███ ███ ░███ ║
riverise-fliter-0622-v1-mkmlizer: ║ ░███░░███ ░███ ░███████ ░███ ║
riverise-fliter-0622-v1-mkmlizer: ║ ░███ ░░░ ░███ ░███░░███ ░███ ║
riverise-fliter-0622-v1-mkmlizer: ║ ░███ ░███ ░███ ░░███ ░███ ║
riverise-fliter-0622-v1-mkmlizer: ║ █████ █████ █████ ░░████ █████ ║
riverise-fliter-0622-v1-mkmlizer: ║ ░░░░░ ░░░░░ ░░░░░ ░░░░ ░░░░░ ║
riverise-fliter-0622-v1-mkmlizer: ║ ║
riverise-fliter-0622-v1-mkmlizer: ║ Version: 0.29.3 ║
riverise-fliter-0622-v1-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
riverise-fliter-0622-v1-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
riverise-fliter-0622-v1-mkmlizer: ║ https://mk1.ai ║
riverise-fliter-0622-v1-mkmlizer: ║ ║
riverise-fliter-0622-v1-mkmlizer: ║ The license key for the current software has been verified as ║
riverise-fliter-0622-v1-mkmlizer: ║ belonging to: ║
riverise-fliter-0622-v1-mkmlizer: ║ ║
riverise-fliter-0622-v1-mkmlizer: ║ Chai Research Corp. ║
riverise-fliter-0622-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
riverise-fliter-0622-v1-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
riverise-fliter-0622-v1-mkmlizer: ║ ║
riverise-fliter-0622-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
riverise-fliter-0622-v1-mkmlizer: Downloaded to shared memory in 38.803s
riverise-fliter-0622-v1-mkmlizer: Checking if Riverise/fliter_0622 already exists in ChaiML
riverise-fliter-0622-v1-mkmlizer: Creating repo ChaiML/fliter_0622 and uploading /tmp/tmp6i8d0e9w to it
riverise-fliter-0622-v1-mkmlizer: 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:07<00:38, 7.64s/it] 33%|███▎ | 2/6 [00:12<00:23, 5.80s/it] 50%|█████ | 3/6 [00:15<00:14, 4.84s/it] 67%|██████▋ | 4/6 [00:20<00:09, 4.65s/it] 83%|████████▎ | 5/6 [00:23<00:04, 4.32s/it] 100%|██████████| 6/6 [00:24<00:00, 3.18s/it] 100%|██████████| 6/6 [00:24<00:00, 4.15s/it]
riverise-fliter-0622-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp6i8d0e9w, device:0
riverise-fliter-0622-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
riverise-fliter-0622-v1-mkmlizer: quantized model in 30.423s
riverise-fliter-0622-v1-mkmlizer: Processed model Riverise/fliter_0622 in 119.069s
riverise-fliter-0622-v1-mkmlizer: creating bucket guanaco-mkml-models
riverise-fliter-0622-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
riverise-fliter-0622-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/riverise-fliter-0622-v1
riverise-fliter-0622-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/riverise-fliter-0622-v1/config.json
riverise-fliter-0622-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/riverise-fliter-0622-v1/special_tokens_map.json
riverise-fliter-0622-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/riverise-fliter-0622-v1/tokenizer_config.json
riverise-fliter-0622-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/riverise-fliter-0622-v1/tokenizer.json
riverise-fliter-0622-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/riverise-fliter-0622-v1/flywheel_model.0.safetensors
riverise-fliter-0622-v1-mkmlizer: Loading 0: 0%| | 0/363 [00:00<?, ?it/s] Loading 0: 1%|▏ | 5/363 [00:00<00:11, 30.92it/s] Loading 0: 3%|▎ | 12/363 [00:00<00:07, 48.99it/s] Loading 0: 5%|▍ | 18/363 [00:00<00:07, 47.85it/s] Loading 0: 7%|▋ | 24/363 [00:00<00:08, 40.22it/s] Loading 0: 9%|▊ | 31/363 [00:00<00:07, 46.58it/s] Loading 0: 10%|█ | 37/363 [00:00<00:07, 44.60it/s] Loading 0: 12%|█▏ | 42/363 [00:00<00:07, 43.76it/s] Loading 0: 13%|█▎ | 49/363 [00:01<00:06, 49.39it/s] Loading 0: 15%|█▌ | 55/363 [00:01<00:06, 46.54it/s] Loading 0: 17%|█▋ | 61/363 [00:01<00:08, 35.37it/s] Loading 0: 18%|█▊ | 66/363 [00:01<00:08, 35.91it/s] Loading 0: 20%|█▉ | 71/363 [00:01<00:07, 38.05it/s] Loading 0: 21%|██ | 76/363 [00:01<00:07, 38.72it/s] Loading 0: 22%|██▏ | 81/363 [00:01<00:07, 40.01it/s] Loading 0: 24%|██▍ | 87/363 [00:02<00:06, 40.38it/s] Loading 0: 25%|██▌ | 92/363 [00:02<00:06, 40.94it/s] Loading 0: 27%|██▋ | 99/363 [00:02<00:05, 45.60it/s] Loading 0: 29%|██▉ | 105/363 [00:02<00:05, 44.05it/s] Loading 0: 31%|███ | 112/363 [00:02<00:05, 48.55it/s] Loading 0: 32%|███▏ | 117/363 [00:02<00:05, 46.92it/s] Loading 0: 34%|███▍ | 123/363 [00:02<00:05, 42.68it/s] Loading 0: 35%|███▌ | 128/363 [00:03<00:05, 39.77it/s] Loading 0: 37%|███▋ | 134/363 [00:03<00:05, 43.69it/s] Loading 0: 38%|███▊ | 139/363 [00:03<00:05, 43.17it/s] Loading 0: 40%|███▉ | 144/363 [00:03<00:07, 28.60it/s] Loading 0: 41%|████ | 149/363 [00:03<00:07, 30.49it/s] Loading 0: 43%|████▎ | 156/363 [00:03<00:05, 37.84it/s] Loading 0: 44%|████▍ | 161/363 [00:03<00:05, 39.28it/s] Loading 0: 46%|████▌ | 166/363 [00:04<00:05, 38.40it/s] Loading 0: 47%|████▋ | 171/363 [00:04<00:04, 39.88it/s] Loading 0: 48%|████▊ | 176/363 [00:04<00:05, 33.88it/s] Loading 0: 50%|█████ | 183/363 [00:04<00:04, 41.01it/s] Loading 0: 52%|█████▏ | 188/363 [00:04<00:04, 41.27it/s] Loading 0: 53%|█████▎ | 193/363 [00:04<00:04, 41.20it/s] Loading 0: 55%|█████▍ | 198/363 [00:04<00:03, 41.35it/s] Loading 0: 56%|█████▌ | 203/363 [00:05<00:04, 32.86it/s] Loading 0: 58%|█████▊ | 210/363 [00:05<00:03, 39.82it/s] Loading 0: 59%|█████▉ | 215/363 [00:05<00:03, 39.88it/s] Loading 0: 61%|██████ | 220/363 [00:05<00:03, 42.25it/s] Loading 0: 62%|██████▏ | 225/363 [00:05<00:05, 27.02it/s] Loading 0: 63%|██████▎ | 230/363 [00:05<00:04, 29.51it/s] Loading 0: 65%|██████▌ | 237/363 [00:06<00:03, 36.80it/s] Loading 0: 67%|██████▋ | 242/363 [00:06<00:03, 37.70it/s] Loading 0: 68%|██████▊ | 247/363 [00:06<00:03, 38.63it/s] Loading 0: 70%|██████▉ | 253/363 [00:06<00:02, 38.86it/s] Loading 0: 71%|███████ | 258/363 [00:06<00:02, 38.72it/s] Loading 0: 73%|███████▎ | 264/363 [00:06<00:02, 42.28it/s] Loading 0: 74%|███████▍ | 269/363 [00:06<00:02, 42.24it/s] Loading 0: 75%|███████▌ | 274/363 [00:06<00:02, 42.77it/s] Loading 0: 77%|███████▋ | 279/363 [00:07<00:01, 44.27it/s] Loading 0: 78%|███████▊ | 284/363 [00:07<00:02, 36.33it/s] Loading 0: 80%|████████ | 291/363 [00:07<00:01, 43.21it/s] Loading 0: 82%|████████▏ | 296/363 [00:07<00:01, 43.65it/s] Loading 0: 83%|████████▎ | 302/363 [00:07<00:01, 47.65it/s] Loading 0: 85%|████████▍ | 308/363 [00:08<00:02, 23.61it/s] Loading 0: 86%|████████▌ | 312/363 [00:08<00:02, 24.32it/s] Loading 0: 88%|████████▊ | 320/363 [00:08<00:01, 32.96it/s] Loading 0: 90%|████████▉ | 326/363 [00:08<00:01, 34.98it/s] Loading 0: 91%|█████████ | 331/363 [00:08<00:00, 36.18it/s] Loading 0: 93%|█████████▎| 338/363 [00:08<00:00, 41.92it/s] Loading 0: 95%|█████████▍| 344/363 [00:08<00:00, 41.43it/s] Loading 0: 96%|█████████▌| 349/363 [00:09<00:00, 39.80it/s] Loading 0: 98%|█████████▊| 355/363 [00:09<00:00, 43.61it/s] Loading 0: 99%|█████████▉| 360/363 [00:09<00:00, 42.23it/s]
Job riverise-fliter-0622-v1-mkmlizer completed after 147.23s with status: succeeded
Stopping job with name riverise-fliter-0622-v1-mkmlizer
Pipeline stage MKMLizer completed in 147.90s
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 riverise-fliter-0622-v1
Waiting for inference service riverise-fliter-0622-v1 to be ready
Inference service riverise-fliter-0622-v1 ready after 140.50207996368408s
Pipeline stage MKMLDeployer completed in 141.08s
run pipeline stage %s
Running pipeline stage StressChecker
HTTPConnectionPool(host='guanaco-submitter.guanaco-backend.k2.chaiverse.com', port=80): Read timed out. (read timeout=20)
Received unhealthy response to inference request!
Received healthy response to inference request in 2.2987754344940186s
Received healthy response to inference request in 2.159072160720825s
Received healthy response to inference request in 1.091817855834961s
Received healthy response to inference request in 1.6853795051574707s
5 requests
1 failed requests
5th percentile: 1.2105301856994628
10th percentile: 1.3292425155639649
20th percentile: 1.5666671752929688
30th percentile: 1.7801180362701416
40th percentile: 1.9695950984954835
50th percentile: 2.159072160720825
60th percentile: 2.2149534702301024
70th percentile: 2.27083477973938
80th percentile: 5.90810322761536
90th percentile: 13.126758813858034
95th percentile: 16.736086606979367
99th percentile: 19.62354884147644
mean time: 5.5160918712615965
%s, retrying in %s seconds...
Received healthy response to inference request in 1.527836561203003s
Received healthy response to inference request in 1.9148821830749512s
Received healthy response to inference request in 1.8284966945648193s
Received healthy response to inference request in 1.7235231399536133s
Received healthy response to inference request in 1.713977575302124s
5 requests
0 failed requests
5th percentile: 1.5650647640228272
10th percentile: 1.6022929668426513
20th percentile: 1.6767493724822997
30th percentile: 1.715886688232422
40th percentile: 1.7197049140930176
50th percentile: 1.7235231399536133
60th percentile: 1.7655125617980958
70th percentile: 1.807501983642578
80th percentile: 1.8457737922668458
90th percentile: 1.8803279876708985
95th percentile: 1.8976050853729247
99th percentile: 1.9114267635345459
mean time: 1.741743230819702
Pipeline stage StressChecker completed in 39.22s
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 0.75s
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 0.71s
Shutdown handler de-registered
riverise-fliter-0622_v1 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
Pipeline stage OfflineFamilyFriendlyScorer completed in 2897.92s
Shutdown handler de-registered
riverise-fliter-0622_v1 status is now inactive due to auto deactivation removed underperforming models
riverise-fliter-0622_v1 status is now torndown due to DeploymentManager action