zonemercy-base-story-v1

submission_id: zonemercy-base-story-v1_v3
developer_uid: zonemercy
best_of: 2
celo_rating: 1200.38
display_name: 0906stv1-2
family_friendly_score: 0.0
formatter: {'memory_template': " Write a slice of story that takes place over the course of a single day in Bot's life. Use stream-of-consciousness narration to explore the character's thoughts and perceptions. Include poetic, impressionistic descriptions of the character's surroundings and sensations. Weave in memories and reflections that provide insight into the Bot's past and inner life. The scene should feel like part of a lived-in world, with the scene naturally existing in a wider story.\n Bot's Name: {bot_name}\nBot's Persona: {memory}\n####\n ", 'prompt_template': '', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot:', 'truncate_by_message': False}
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.05, 'top_k': 100, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['</s>', 'Bot:', 'User:', 'You:'], 'max_input_tokens': 1024, 'best_of': 2, 'max_output_tokens': 128}
gpu_counts: {'NVIDIA RTX A5000': 1}
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: zonemercy/Base-Story-v1
latencies: [{'batch_size': 1, 'throughput': 0.3604972790627228, 'latency_mean': 2.773845522403717, 'latency_p50': 2.7667810916900635, 'latency_p90': 2.9481331586837767}, {'batch_size': 3, 'throughput': 0.8347426530489408, 'latency_mean': 3.579602019786835, 'latency_p50': 3.5999209880828857, 'latency_p90': 3.759902572631836}, {'batch_size': 5, 'throughput': 1.1730322724718096, 'latency_mean': 4.242963244915009, 'latency_p50': 4.209678888320923, 'latency_p90': 4.63315634727478}, {'batch_size': 6, 'throughput': 1.2785828266456194, 'latency_mean': 4.658372023105621, 'latency_p50': 4.675348281860352, 'latency_p90': 4.984981179237366}, {'batch_size': 8, 'throughput': 1.4718889412898897, 'latency_mean': 5.396529558897019, 'latency_p50': 5.413252949714661, 'latency_p90': 5.8262183427810665}, {'batch_size': 10, 'throughput': 1.5738137365883824, 'latency_mean': 6.295116145610809, 'latency_p50': 6.285029888153076, 'latency_p90': 6.953094172477722}]
max_input_tokens: 1024
max_output_tokens: 128
model_architecture: MistralForCausalLM
model_group: zonemercy/Base-Story-v1
model_name: 0906stv1-2
model_num_parameters: 12772070400.0
model_repo: zonemercy/Base-Story-v1
model_size: 13B
num_battles: 10024
num_wins: 4621
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 0.91
timestamp: 2024-09-06T11:36:54+00:00
us_pacific_date: 2024-09-06
win_ratio: 0.46099361532322425
Download Preference Data
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Shutdown handler not registered because Python interpreter is not running in the main thread
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Running pipeline stage MKMLizer
Starting job with name zonemercy-base-story-v1-v3-mkmlizer
Waiting for job on zonemercy-base-story-v1-v3-mkmlizer to finish
zonemercy-base-story-v1-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
zonemercy-base-story-v1-v3-mkmlizer: ║     _____            __           __                                ║
zonemercy-base-story-v1-v3-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
zonemercy-base-story-v1-v3-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
zonemercy-base-story-v1-v3-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
zonemercy-base-story-v1-v3-mkmlizer: ║       /___/                                                         ║
zonemercy-base-story-v1-v3-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v3-mkmlizer: ║  Version: 0.10.1                                                    ║
zonemercy-base-story-v1-v3-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
zonemercy-base-story-v1-v3-mkmlizer: ║  https://mk1.ai                                                     ║
zonemercy-base-story-v1-v3-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
zonemercy-base-story-v1-v3-mkmlizer: ║  belonging to:                                                      ║
zonemercy-base-story-v1-v3-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v3-mkmlizer: ║  Chai Research Corp.                                                ║
zonemercy-base-story-v1-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
zonemercy-base-story-v1-v3-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
zonemercy-base-story-v1-v3-mkmlizer: ║                                                                     ║
zonemercy-base-story-v1-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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zonemercy-base-story-v1-v3-mkmlizer: Downloaded to shared memory in 90.991s
zonemercy-base-story-v1-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpmv6_103e, device:0
zonemercy-base-story-v1-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
zonemercy-base-story-v1-v3-mkmlizer: quantized model in 40.990s
zonemercy-base-story-v1-v3-mkmlizer: Processed model zonemercy/Base-Story-v1 in 131.982s
zonemercy-base-story-v1-v3-mkmlizer: creating bucket guanaco-mkml-models
zonemercy-base-story-v1-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
zonemercy-base-story-v1-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/zonemercy-base-story-v1-v3
zonemercy-base-story-v1-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v3/config.json
zonemercy-base-story-v1-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v3/special_tokens_map.json
zonemercy-base-story-v1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v3/tokenizer_config.json
zonemercy-base-story-v1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/zonemercy-base-story-v1-v3/tokenizer.json
zonemercy-base-story-v1-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/zonemercy-base-story-v1-v3/flywheel_model.0.safetensors
zonemercy-base-story-v1-v3-mkmlizer: 
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Job zonemercy-base-story-v1-v3-mkmlizer completed after 156.55s with status: succeeded
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Received healthy response to inference request in 3.2396702766418457s
Received healthy response to inference request in 2.757504940032959s
Received healthy response to inference request in 3.1167824268341064s
Received healthy response to inference request in 1.241852045059204s
Received healthy response to inference request in 3.2559447288513184s
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5th percentile: 1.544982624053955
10th percentile: 1.848113203048706
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70th percentile: 3.2150927066802977
80th percentile: 3.2429251670837402
90th percentile: 3.2494349479675293
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/zonemercy-base-story-v1-v3-profiler-predictor-00001-deploy8hshs:/code/chaiverse_profiler_1725623138 --namespace tenant-chaiml-guanaco
kubectl exec -it zonemercy-base-story-v1-v3-profiler-predictor-00001-deploy8hshs --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725623138 && python profiles.py profile --best_of_n 2 --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 1024 --output_tokens 128 --summary /code/chaiverse_profiler_1725623138/summary.json'
kubectl exec -it zonemercy-base-story-v1-v3-profiler-predictor-00001-deploy8hshs --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725623138/summary.json'
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