albertwang8192-2025-07-11-7

developer_uid: RandomForest1024

submission_id: albertwang8192-2025-07-11-7_v3

model_name: 2025-07-11_7_v3

model_group: AlbertWang8192/2025-07-1

status: torndown

timestamp: 2025-07-12T14:30:27+00:00

num_battles: 8690

num_wins: 4179

celo_rating: 1271.22

family_friendly_score: 0.5476

family_friendly_standard_error: 0.007038952194751716

submission_type: basic

model_repo: AlbertWang8192/2025-07-11_7

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': 0.5844584768953183, 'latency_mean': 1.7108610498905181, 'latency_p50': 1.7111541032791138, 'latency_p90': 1.8849950075149535}, {'batch_size': 3, 'throughput': 1.049814753851908, 'latency_mean': 2.850958148241043, 'latency_p50': 2.8577016592025757, 'latency_p90': 3.13472204208374}, {'batch_size': 5, 'throughput': 1.2530576992621847, 'latency_mean': 3.9641120374202727, 'latency_p50': 3.930416703224182, 'latency_p90': 4.418447518348693}, {'batch_size': 6, 'throughput': 1.3098388877531946, 'latency_mean': 4.560943905115128, 'latency_p50': 4.598960041999817, 'latency_p90': 5.131461977958679}, {'batch_size': 8, 'throughput': 1.3733984480684376, 'latency_mean': 5.792725168466568, 'latency_p50': 5.79697585105896, 'latency_p90': 6.5579674482345585}, {'batch_size': 10, 'throughput': 1.3948147568932696, 'latency_mean': 7.103303588628769, 'latency_p50': 7.1738340854644775, 'latency_p90': 7.9067772865295405}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: 2025-07-11_7_v3

is_internal_developer: False

language_model: AlbertWang8192/2025-07-11_7

model_size: 13B

ranking_group: single

throughput_3p7s: 1.22

us_pacific_date: 2025-07-12

win_ratio: 0.480897583429229

generation_params: {'temperature': 0.5, 'top_p': 0.95, 'min_p': 0.025, 'top_k': 60, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['<|im_start|>', '<|im_end|>', '\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 albertwang8192-2025-07-11-7-v3-mkmlizer
Waiting for job on albertwang8192-2025-07-11-7-v3-mkmlizer to finish
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albertwang8192-2025-07-11-7-v3-mkmlizer: ║                                                                     ║
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albertwang8192-2025-07-11-7-v3-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  Version: 0.29.15                                                   ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  https://mk1.ai                                                     ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  belonging to:                                                      ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  Chai Research Corp.                                                ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ║                                                                     ║
albertwang8192-2025-07-11-7-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-11-7-v3-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`
albertwang8192-2025-07-11-7-v3-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`
albertwang8192-2025-07-11-7-v3-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`
albertwang8192-2025-07-11-7-v3-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`
albertwang8192-2025-07-11-7-v3-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`
albertwang8192-2025-07-11-7-v3-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`
albertwang8192-2025-07-11-7-v3-mkmlizer: Downloaded to shared memory in 29.742s
albertwang8192-2025-07-11-7-v3-mkmlizer: Checking if AlbertWang8192/2025-07-11_7 already exists in ChaiML
albertwang8192-2025-07-11-7-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpan0e35wr, device:0
albertwang8192-2025-07-11-7-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-11-7-v3-mkmlizer: quantized model in 31.080s
albertwang8192-2025-07-11-7-v3-mkmlizer: Processed model AlbertWang8192/2025-07-11_7 in 60.906s
albertwang8192-2025-07-11-7-v3-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-11-7-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-11-7-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v3/nvidia
albertwang8192-2025-07-11-7-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v3/nvidia/special_tokens_map.json
albertwang8192-2025-07-11-7-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v3/nvidia/config.json
albertwang8192-2025-07-11-7-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v3/nvidia/tokenizer_config.json
albertwang8192-2025-07-11-7-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v3/nvidia/tokenizer.json
albertwang8192-2025-07-11-7-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-11-7-v3/nvidia/flywheel_model.0.safetensors
albertwang8192-2025-07-11-7-v3-mkmlizer: 
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Job albertwang8192-2025-07-11-7-v3-mkmlizer completed after 85.81s with status: succeeded
Stopping job with name albertwang8192-2025-07-11-7-v3-mkmlizer
Pipeline stage MKMLizer completed in 86.38s
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Running pipeline stage MKMLTemplater
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Creating inference service albertwang8192-2025-07-11-7-v3
Waiting for inference service albertwang8192-2025-07-11-7-v3 to be ready
Inference service albertwang8192-2025-07-11-7-v3 ready after 210.84744668006897s
Pipeline stage MKMLDeployer completed in 211.35s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.86098313331604s
Received healthy response to inference request in 1.601372241973877s
Received healthy response to inference request in 1.5607707500457764s
Received healthy response to inference request in 1.82501220703125s
Received healthy response to inference request in 1.530888319015503s
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5th percentile: 1.5368648052215577
10th percentile: 1.5428412914276124
20th percentile: 1.5547942638397216
30th percentile: 1.5688910484313965
40th percentile: 1.5851316452026367
50th percentile: 1.601372241973877
60th percentile: 1.690828227996826
70th percentile: 1.7802842140197754
80th percentile: 2.032206392288208
90th percentile: 2.4465947628021243
95th percentile: 2.653788948059082
99th percentile: 2.8195442962646484
mean time: 1.8758053302764892
Pipeline stage StressChecker completed in 11.14s
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