submission_id: cycy233-l3-p-v4-c1_v2
developer_uid: shiroe40
best_of: 16
celo_rating: 1247.27
display_name: auto
family_friendly_score: 0.0
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{bot_name}'s Persona: {memory}\n\n", 'prompt_template': '{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}: {message}<|eot_id|>', 'user_template': '<|start_header_id|>user<|end_header_id|>\n\n{user_name}: {message}<|eot_id|>', 'response_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 1.0, 'top_p': 0.9, 'min_p': 0.05, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['<|end_header_id|>', '<|eot_id|>'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: cycy233/L3-p-v4-c1
latencies: [{'batch_size': 1, 'throughput': 0.9009500860048005, 'latency_mean': 1.1098773574829102, 'latency_p50': 1.1069269180297852, 'latency_p90': 1.2410840034484862}, {'batch_size': 4, 'throughput': 1.7662162769625598, 'latency_mean': 2.2603618967533112, 'latency_p50': 2.2462953329086304, 'latency_p90': 2.5273807525634764}, {'batch_size': 5, 'throughput': 1.8793104637572873, 'latency_mean': 2.648704679012299, 'latency_p50': 2.6193888187408447, 'latency_p90': 2.9635923147201537}, {'batch_size': 8, 'throughput': 1.9860749962189654, 'latency_mean': 3.998525743484497, 'latency_p50': 3.988560199737549, 'latency_p90': 4.504106616973877}, {'batch_size': 10, 'throughput': 2.0235496120793046, 'latency_mean': 4.898951317071915, 'latency_p50': 4.8888258934021, 'latency_p90': 5.6428800344467165}, {'batch_size': 12, 'throughput': 2.0146477717417923, 'latency_mean': 5.87872132062912, 'latency_p50': 5.890021085739136, 'latency_p90': 6.684669446945191}, {'batch_size': 15, 'throughput': 2.0052045581354565, 'latency_mean': 7.336774439811706, 'latency_p50': 7.4243247509002686, 'latency_p90': 8.16950557231903}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: cycy233/L3-p-v4-c1
model_name: auto
model_num_parameters: 8030261248.0
model_repo: cycy233/L3-p-v4-c1
model_size: 8B
num_battles: 12120
num_wins: 6095
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.98
timestamp: 2024-09-13T02:31:13+00:00
us_pacific_date: 2024-09-12
win_ratio: 0.5028877887788779
Download Preference Data
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Running pipeline stage MKMLizer
Starting job with name cycy233-l3-p-v4-c1-v2-mkmlizer
Waiting for job on cycy233-l3-p-v4-c1-v2-mkmlizer to finish
cycy233-l3-p-v4-c1-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ _____ __ __ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ /___/ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ Version: 0.10.1 ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ https://mk1.ai ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ belonging to: ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ Chai Research Corp. ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ║ ║
cycy233-l3-p-v4-c1-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-l3-p-v4-c1-v2-mkmlizer: Downloaded to shared memory in 27.863s
cycy233-l3-p-v4-c1-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp9gniaz9j, device:0
cycy233-l3-p-v4-c1-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cycy233-l3-p-v4-c1-v2-mkmlizer: quantized model in 26.082s
cycy233-l3-p-v4-c1-v2-mkmlizer: Processed model cycy233/L3-p-v4-c1 in 53.945s
cycy233-l3-p-v4-c1-v2-mkmlizer: creating bucket guanaco-mkml-models
cycy233-l3-p-v4-c1-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-l3-p-v4-c1-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v2
cycy233-l3-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v2/special_tokens_map.json
cycy233-l3-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v2/tokenizer_config.json
cycy233-l3-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v2/config.json
cycy233-l3-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v2/tokenizer.json
cycy233-l3-p-v4-c1-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cycy233-l3-p-v4-c1-v2/flywheel_model.0.safetensors
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Job cycy233-l3-p-v4-c1-v2-mkmlizer completed after 75.82s with status: succeeded
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Received healthy response to inference request in 2.527426242828369s
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Received healthy response to inference request in 1.9724977016448975s
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5th percentile: 1.6825078964233398
10th percentile: 1.7504802227020264
20th percentile: 1.8864248752593995
30th percentile: 1.9580173015594482
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70th percentile: 2.4164405345916746
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mean time: 2.1750951766967774
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/cycy233-l3-p-v4-c1-v2-profiler-predictor-00001-deployment-htq4h:/code/chaiverse_profiler_1726195151 --namespace tenant-chaiml-guanaco
kubectl exec -it cycy233-l3-p-v4-c1-v2-profiler-predictor-00001-deployment-htq4h --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726195151 && python profiles.py profile --best_of_n 16 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 512 --output_tokens 64 --summary /code/chaiverse_profiler_1726195151/summary.json'
kubectl exec -it cycy233-l3-p-v4-c1-v2-profiler-predictor-00001-deployment-htq4h --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726195151/summary.json'
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