submission_id: nousresearch-meta-llama-3-8b_v8
developer_uid: end_to_end_test
best_of: 16
celo_rating: 1102.99
display_name: nousresearch-meta-llama-3-8b_v8
family_friendly_score: 0.0
formatter: {'memory_template': 'character: {bot_name} {memory}\n', 'prompt_template': '{prompt}', 'bot_template': '{bot_name}: {message}', 'user_template': '{user_name}: {message}', 'response_template': '{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 1.0, 'top_p': 0.99, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
ineligible_reason: model is only for e2e test
is_internal_developer: True
language_model: NousResearch/Meta-Llama-3-8B
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: NousResearch/Meta-Llama-
model_name: nousresearch-meta-llama-3-8b_v8
model_num_parameters: 8030261248.0
model_repo: NousResearch/Meta-Llama-3-8B
model_size: 8B
num_battles: 23196
num_wins: 9404
ranking_group: single
reward_formatter: {'bot_template': '{bot_name}: {message}', 'memory_template': 'character: {bot_name} {memory}\n', 'prompt_template': '{prompt}', 'response_template': '{bot_name}:', 'truncate_by_message': False, 'user_template': '{user_name}: {message}'}
reward_repo: ChaiML/reward_models_100_170000000_cp_498032
status: torndown
submission_type: basic
timestamp: 2024-05-04T03:21:17+00:00
us_pacific_date: 2024-05-03
win_ratio: 0.4054147266770133
Resubmit model
Running pipeline stage MKMLizer
Starting job with name nousresearch-meta-llama-3-8b-v8-mkmlizer
Waiting for job on nousresearch-meta-llama-3-8b-v8-mkmlizer to finish
nousresearch-meta-llama-3-8b-v8-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ /___/ ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ Version: 0.8.10 ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ The license key for the current software has been verified as ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ belonging to: ║
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nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ Chai Research Corp. ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ║ ║
nousresearch-meta-llama-3-8b-v8-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
nousresearch-meta-llama-3-8b-v8-mkmlizer: /opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:131: FutureWarning: 'list_files_info' (from 'huggingface_hub.hf_api') is deprecated and will be removed from version '0.23'. Use `list_repo_tree` and `get_paths_info` instead.
nousresearch-meta-llama-3-8b-v8-mkmlizer: warnings.warn(warning_message, FutureWarning)
nousresearch-meta-llama-3-8b-v8-mkmlizer: Downloaded to shared memory in 40.443s
nousresearch-meta-llama-3-8b-v8-mkmlizer: quantizing model to /dev/shm/model_cache
nousresearch-meta-llama-3-8b-v8-mkmlizer: Saving flywheel model at /dev/shm/model_cache
nousresearch-meta-llama-3-8b-v8-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 45%|████▍ | 130/291 [00:01<00:01, 128.83it/s] Loading 0: 92%|█████████▏| 269/291 [00:02<00:00, 134.56it/s] Loading 0: 99%|█████████▊| 287/291 [00:06<00:00, 29.43it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
nousresearch-meta-llama-3-8b-v8-mkmlizer: quantized model in 17.341s
nousresearch-meta-llama-3-8b-v8-mkmlizer: Processed model NousResearch/Meta-Llama-3-8B in 58.803s
nousresearch-meta-llama-3-8b-v8-mkmlizer: creating bucket guanaco-mkml-models
nousresearch-meta-llama-3-8b-v8-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
nousresearch-meta-llama-3-8b-v8-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/nousresearch-meta-llama-3-8b-v8
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/nousresearch-meta-llama-3-8b-v8/config.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/nousresearch-meta-llama-3-8b-v8/special_tokens_map.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/nousresearch-meta-llama-3-8b-v8/tokenizer_config.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/nousresearch-meta-llama-3-8b-v8/tokenizer.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/nousresearch-meta-llama-3-8b-v8/flywheel_model.0.safetensors
nousresearch-meta-llama-3-8b-v8-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:468: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
nousresearch-meta-llama-3-8b-v8-mkmlizer: warnings.warn(
nousresearch-meta-llama-3-8b-v8-mkmlizer: /opt/conda/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
nousresearch-meta-llama-3-8b-v8-mkmlizer: return self.fget.__get__(instance, owner)()
nousresearch-meta-llama-3-8b-v8-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
nousresearch-meta-llama-3-8b-v8-mkmlizer: Saving duration: 0.079s
nousresearch-meta-llama-3-8b-v8-mkmlizer: Processed model ChaiML/reward_models_100_170000000_cp_498032 in 8.919s
nousresearch-meta-llama-3-8b-v8-mkmlizer: creating bucket guanaco-reward-models
nousresearch-meta-llama-3-8b-v8-mkmlizer: Bucket 's3://guanaco-reward-models/' created
nousresearch-meta-llama-3-8b-v8-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/special_tokens_map.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/config.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/tokenizer_config.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/merges.txt
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/vocab.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/tokenizer.json
nousresearch-meta-llama-3-8b-v8-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/nousresearch-meta-llama-3-8b-v8_reward/reward.tensors
Job nousresearch-meta-llama-3-8b-v8-mkmlizer completed after 347.14s with status: succeeded
Stopping job with name nousresearch-meta-llama-3-8b-v8-mkmlizer
Pipeline stage MKMLizer completed in 348.87s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.45s
Running pipeline stage ISVCDeployer
Creating inference service nousresearch-meta-llama-3-8b-v8
Tearing down inference service nousresearch-meta-llama-3-8b-v8
%s, retrying in %s seconds...
Creating inference service nousresearch-meta-llama-3-8b-v8
Tearing down inference service nousresearch-meta-llama-3-8b-v8
%s, retrying in %s seconds...
Creating inference service nousresearch-meta-llama-3-8b-v8
Tearing down inference service nousresearch-meta-llama-3-8b-v8
DeploymentError('500\nReason: Internal Server Error\nHTTP response headers: HTTPHeaderDict({\'Audit-Id\': \'d3489d8c-1477-45ab-bbd1-f972020e99d2, 635bc53a-6219-4732-975a-ac2a36326d14\', \'Cache-Control\': \'no-cache, private, no-cache, private\', \'Content-Length\': \'229\', \'Content-Type\': \'application/json\', \'Date\': \'Sat, 04 May 2024 03:27:11 GMT\', \'X-Kubernetes-Pf-Flowschema-Uid\': \'71f0b454-4ff1-43ef-b90a-8fc505cec187\', \'X-Kubernetes-Pf-Prioritylevel-Uid\': \'fb8f477e-2340-4820-9790-65b9b3f00867\'})\nHTTP response body: b\'{"kind":"Status","apiVersion":"v1","metadata":{},"status":"Failure","message":"Internal error occurred: error resolving resource","reason":"InternalError","details":{"causes":[{"message":"error resolving resource"}]},"code":500}\\n\'\nOriginal traceback: \n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/dynamic/client.py", line 55, in inner\n resp = func(self, *args, **kwargs)\n\n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/dynamic/client.py", line 270, in request\n api_response = self.client.call_api(\n\n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/client/api_client.py", line 348, in call_api\n return self.__call_api(resource_path, method,\n\n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/client/api_client.py", line 180, in __call_api\n response_data = self.request(\n\n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/client/api_client.py", line 415, in request\n return self.rest_client.DELETE(url,\n\n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/client/rest.py", line 266, in DELETE\n return self.request("DELETE", url,\n\n File "/home/alex/.local/lib/python3.8/site-packages/kubernetes/client/rest.py", line 234, in request\n raise ApiException(http_resp=r)\n')
nousresearch-meta-llama-3-8b_v8 status is now failed due to DeploymentManager action
admin requested tearing down of nousresearch-meta-llama-3-8b_v8
Running pipeline stage ISVCDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage ISVCDeleter completed in 0.13s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key nousresearch-meta-llama-3-8b-v8/config.json from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-3-8b-v8/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-3-8b-v8/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-3-8b-v8/tokenizer.json from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-3-8b-v8/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key nousresearch-meta-llama-3-8b-v8_reward/config.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-3-8b-v8_reward/merges.txt from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-3-8b-v8_reward/reward.tensors from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-3-8b-v8_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-3-8b-v8_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-3-8b-v8_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-3-8b-v8_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 2.63s
nousresearch-meta-llama-3-8b_v8 status is now torndown due to DeploymentManager action
nousresearch-meta-llama-3-8b_v8 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of nousresearch-meta-llama-3-8b_v8
Running pipeline stage ISVCDeleter
Pipeline stage %s skipped, reason=%s
Pipeline stage ISVCDeleter completed in 0.09s
Running pipeline stage MKMLModelDeleter
Pipeline stage %s skipped, reason=%s
Pipeline stage MKMLModelDeleter completed in 0.07s
nousresearch-meta-llama-3-8b_v8 status is now torndown due to DeploymentManager action