submission_id: chaiml-albert-dpo-0912-v_2353_v3
developer_uid: azuruce
alignment_samples: 11633
alignment_score: 2.69247679531698
best_of: 8
celo_rating: 1125.11
display_name: ai-improved
formatter: {'memory_template': 'Bot Name: {bot_name}\n####\n', 'prompt_template': '', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot:', 'truncate_by_message': False}
generation_params: {'temperature': 0.9, 'top_p': 1.0, 'min_p': 0.05, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>', '###', 'Bot:', 'User:', 'You:', '<|im_end|>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: True
language_model: ChaiML/albert_dpo_0912_virgo_edit_improved
latencies: [{'batch_size': 1, 'throughput': 0.6245591766981019, 'latency_mean': 1.601034265756607, 'latency_p50': 1.588258981704712, 'latency_p90': 1.7865989446640014}, {'batch_size': 3, 'throughput': 1.0786275990435643, 'latency_mean': 2.7714994561672213, 'latency_p50': 2.759498953819275, 'latency_p90': 3.0362457275390624}, {'batch_size': 5, 'throughput': 1.2466576081194531, 'latency_mean': 4.0014718770980835, 'latency_p50': 3.999752998352051, 'latency_p90': 4.505278944969177}, {'batch_size': 6, 'throughput': 1.2630663556108874, 'latency_mean': 4.728247499465942, 'latency_p50': 4.783358216285706, 'latency_p90': 5.305705213546753}, {'batch_size': 8, 'throughput': 1.250182275227513, 'latency_mean': 6.35460626244545, 'latency_p50': 6.397478699684143, 'latency_p90': 7.209334754943848}, {'batch_size': 10, 'throughput': 1.2225470170430668, 'latency_mean': 8.139923516511917, 'latency_p50': 8.213266134262085, 'latency_p90': 9.15675799846649}]
max_input_tokens: 1024
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: ChaiML/albert_dpo_0912_v
model_name: ai-improved
model_num_parameters: 12772070400.0
model_repo: ChaiML/albert_dpo_0912_virgo_edit_improved
model_size: 13B
num_battles: 11632
num_wins: 3826
propriety_score: 0.7476635514018691
propriety_total_count: 1070.0
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.22
timestamp: 2024-09-15T05:33:33+00:00
us_pacific_date: 2024-09-14
win_ratio: 0.32892022008253097
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name chaiml-albert-dpo-0912-v-2353-v3-mkmlizer
Waiting for job on chaiml-albert-dpo-0912-v-2353-v3-mkmlizer to finish
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ _____ __ __ ║
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chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ Version: 0.10.1 ║
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ https://mk1.ai ║
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ ║
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chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ belonging to: ║
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chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ Chai Research Corp. ║
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
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chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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Failed to get response for submission blend_hokok_2024-09-09: ('http://neversleep-noromaid-v0-8068-v150-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
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Failed to get response for submission blend_hokok_2024-09-09: ('http://neversleep-noromaid-v0-8068-v150-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: Downloaded to shared memory in 55.242s
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpzeffwkxz, device:0
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: quantized model in 40.672s
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: Processed model ChaiML/albert_dpo_0912_virgo_edit_improved in 95.914s
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: creating bucket guanaco-mkml-models
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-albert-dpo-0912-v-2353-v3
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-albert-dpo-0912-v-2353-v3/config.json
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-albert-dpo-0912-v-2353-v3/special_tokens_map.json
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-albert-dpo-0912-v-2353-v3/tokenizer_config.json
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-albert-dpo-0912-v-2353-v3/tokenizer.json
chaiml-albert-dpo-0912-v-2353-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-albert-dpo-0912-v-2353-v3/flywheel_model.0.safetensors
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Job chaiml-albert-dpo-0912-v-2353-v3-mkmlizer completed after 126.75s with status: succeeded
Stopping job with name chaiml-albert-dpo-0912-v-2353-v3-mkmlizer
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Creating inference service chaiml-albert-dpo-0912-v-2353-v3
Waiting for inference service chaiml-albert-dpo-0912-v-2353-v3 to be ready
Failed to get response for submission blend_hokok_2024-09-09: ('http://neversleep-noromaid-v0-8068-v150-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
Failed to get response for submission blend_hokok_2024-09-09: ('http://neversleep-noromaid-v0-8068-v150-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
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Inference service chaiml-albert-dpo-0912-v-2353-v3 ready after 170.61683917045593s
Pipeline stage MKMLDeployer completed in 171.93s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.3099896907806396s
Received healthy response to inference request in 1.5224871635437012s
Received healthy response to inference request in 1.233001470565796s
Received healthy response to inference request in 1.3540418148040771s
Received healthy response to inference request in 1.7074291706085205s
5 requests
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5th percentile: 1.2572095394134521
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90th percentile: 2.068965482711792
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mean time: 1.625389862060547
Pipeline stage StressChecker completed in 8.79s
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Inference service chaiml-albert-dpo-0912-v-2353-v3-profiler ready after 170.4178433418274s
Pipeline stage MKMLProfilerDeployer completed in 173.27s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/chaiml-albert-dpo-09dbec6b564e1b62b7ca3b41c51854c296-deplozxckk:/code/chaiverse_profiler_1726378940 --namespace tenant-chaiml-guanaco
kubectl exec -it chaiml-albert-dpo-09dbec6b564e1b62b7ca3b41c51854c296-deplozxckk --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726378940 && python profiles.py profile --best_of_n 8 --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 64 --summary /code/chaiverse_profiler_1726378940/summary.json'
kubectl exec -it chaiml-albert-dpo-09dbec6b564e1b62b7ca3b41c51854c296-deplozxckk --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726378940/summary.json'
Pipeline stage MKMLProfilerRunner completed in 1158.19s
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Running pipeline stage MKMLProfilerDeleter
Checking if service chaiml-albert-dpo-0912-v-2353-v3-profiler is running
Tearing down inference service chaiml-albert-dpo-0912-v-2353-v3-profiler
Service chaiml-albert-dpo-0912-v-2353-v3-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 6.22s
Shutdown handler de-registered
chaiml-albert-dpo-0912-v_2353_v3 status is now inactive due to auto deactivation removed underperforming models