developer_uid: cloudyu
submission_id: cloudyu-nemo-dpo-v19_v8
model_name: cloudyu-nemo-dpo-v19_v1
model_group: cloudyu/Nemo-DPO-V19
status: inactive
timestamp: 2024-12-16T22:40:47+00:00
num_battles: 14087
num_wins: 7339
celo_rating: 1278.27
family_friendly_score: 0.5602
family_friendly_standard_error: 0.007019629050028214
submission_type: basic
model_repo: cloudyu/Nemo-DPO-V19
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
latencies: [{'batch_size': 1, 'throughput': 0.6100205038933995, 'latency_mean': 1.6392014062404632, 'latency_p50': 1.6375292539596558, 'latency_p90': 1.8027545928955078}, {'batch_size': 3, 'throughput': 1.1112914878547253, 'latency_mean': 2.6897326469421388, 'latency_p50': 2.6804864406585693, 'latency_p90': 2.973587918281555}, {'batch_size': 5, 'throughput': 1.352116136217336, 'latency_mean': 3.682483192682266, 'latency_p50': 3.7212717533111572, 'latency_p90': 4.113451814651489}, {'batch_size': 6, 'throughput': 1.4113040521630644, 'latency_mean': 4.227642590999603, 'latency_p50': 4.217344403266907, 'latency_p90': 4.697124934196472}, {'batch_size': 8, 'throughput': 1.4872431400745103, 'latency_mean': 5.346924097537994, 'latency_p50': 5.295405268669128, 'latency_p90': 6.087139582633972}, {'batch_size': 10, 'throughput': 1.5107341044165483, 'latency_mean': 6.573555170297623, 'latency_p50': 6.610309958457947, 'latency_p90': 7.487394595146179}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: cloudyu-nemo-dpo-v19_v1
is_internal_developer: False
language_model: cloudyu/Nemo-DPO-V19
model_size: 13B
ranking_group: single
throughput_3p7s: 1.36
us_pacific_date: 2024-12-16
win_ratio: 0.5209767871086818
generation_params: {'temperature': 1.0, 'top_p': 0.95, 'min_p': 0.05, 'top_k': 80, '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 cloudyu-nemo-dpo-v19-v8-mkmlizer
Waiting for job on cloudyu-nemo-dpo-v19-v8-mkmlizer to finish
cloudyu-nemo-dpo-v19-v8-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ _____ __ __ ║
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cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
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cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ /___/ ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ Version: 0.11.12 ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ https://mk1.ai ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ The license key for the current software has been verified as ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ belonging to: ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ Chai Research Corp. ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ Expiration: 2025-01-15 23:59:59 ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ║ ║
cloudyu-nemo-dpo-v19-v8-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cloudyu-nemo-dpo-v19-v8-mkmlizer: Downloaded to shared memory in 35.166s
cloudyu-nemo-dpo-v19-v8-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp3w2uxwp9, device:0
cloudyu-nemo-dpo-v19-v8-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cloudyu-nemo-dpo-v19-v8-mkmlizer: quantized model in 36.501s
cloudyu-nemo-dpo-v19-v8-mkmlizer: Processed model cloudyu/Nemo-DPO-V19 in 71.667s
cloudyu-nemo-dpo-v19-v8-mkmlizer: creating bucket guanaco-mkml-models
cloudyu-nemo-dpo-v19-v8-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cloudyu-nemo-dpo-v19-v8-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cloudyu-nemo-dpo-v19-v8
cloudyu-nemo-dpo-v19-v8-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cloudyu-nemo-dpo-v19-v8/special_tokens_map.json
cloudyu-nemo-dpo-v19-v8-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cloudyu-nemo-dpo-v19-v8/config.json
cloudyu-nemo-dpo-v19-v8-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cloudyu-nemo-dpo-v19-v8/tokenizer_config.json
cloudyu-nemo-dpo-v19-v8-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cloudyu-nemo-dpo-v19-v8/tokenizer.json
cloudyu-nemo-dpo-v19-v8-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cloudyu-nemo-dpo-v19-v8/flywheel_model.0.safetensors
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Job cloudyu-nemo-dpo-v19-v8-mkmlizer completed after 94.32s with status: succeeded
Stopping job with name cloudyu-nemo-dpo-v19-v8-mkmlizer
Pipeline stage MKMLizer completed in 94.86s
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Creating inference service cloudyu-nemo-dpo-v19-v8
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Inference service cloudyu-nemo-dpo-v19-v8 ready after 220.81348299980164s
Pipeline stage MKMLDeployer completed in 221.34s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.3664777278900146s
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Received healthy response to inference request in 1.6593928337097168s
Received healthy response to inference request in 1.6799182891845703s
Received healthy response to inference request in 1.8837220668792725s
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5th percentile: 1.6634979248046875
10th percentile: 1.6676030158996582
20th percentile: 1.6758131980895996
30th percentile: 1.6951711654663086
40th percentile: 1.725676918029785
50th percentile: 1.7561826705932617
60th percentile: 1.807198429107666
70th percentile: 1.8582141876220704
80th percentile: 1.980273199081421
90th percentile: 2.173375463485718
95th percentile: 2.269926595687866
99th percentile: 2.3471675014495847
mean time: 1.8691387176513672
Pipeline stage StressChecker completed in 10.67s
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