Runtime error while deploying on Sagemaker
Hi, can someone help me debug this?
I am trying to deploy wizard coder on Sagemaker using the recommended deploy code, I am getting the following error -
[RuntimeError: found uninitialized parameters in model : ['transformer.h.0.attn.c_attn.weight', 'transformer.h.0.attn.c_proj.weight', 'transformer.h.0.mlp.c_fc.weight', 'transformer.h.0.mlp.c_proj.weight', 'transformer.h.1.attn.c_attn.weight', ](RuntimeError: found uninitialized parameters in model : ['transformer.h.0.attn.c_attn.weight', 'transformer.h.0.attn.c_proj.weight', 'transformer.h.0.mlp.c_fc.weight', 'transformer.h.0.mlp.c_proj.weight', 'transformer.h.1.attn.c_attn.weight', 'transformer.h.1.attn.c_proj.weight', 'transformer.h.1.mlp.c_fc.weight', 'transformer.h.1.mlp.c_proj.weight', 'transformer.h.2.attn.c_attn.weight', 'transformer.h.2.attn.c_proj.weight', 'transformer.h.2.mlp.c_fc.weight', 'transformer.h.2.mlp.c_proj.weight', 'transformer.h.3.attn.c_attn.weight', 'transformer.h.3.attn.c_proj.weight', 'transformer.h.3.mlp.c_fc.weight', 'transformer.h.3.mlp.c_proj.weight'........
Recommended Deploy code -
import json
import sagemaker
import boto3
from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri
try:
role = sagemaker.get_execution_role()
except ValueError:
iam = boto3.client('iam')
role = iam.get_role(RoleName='sagemaker_execution_role')['Role']['Arn']
Hub Model configuration. https://huggingface.co/models
hub = {
'HF_MODEL_ID':'TheBloke/WizardCoder-15B-1.0-GPTQ',
'SM_NUM_GPUS': json.dumps(1)
}
create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
image_uri=get_huggingface_llm_image_uri("huggingface",version="0.8.2"),
env=hub,
role=role,
)
deploy model to SageMaker Inference
predictor = huggingface_model.deploy(
initial_instance_count=1,
instance_type="ml.g5.2xlarge",
container_startup_health_check_timeout=300,
)
send request
predictor.predict({
"inputs": "My name is Julien and I like to",
})
You need to specify the HF token like this:
hub = {
'HF_MODEL_ID':'WizardLM/WizardCoder-15B-V1.0',
'SM_NUM_GPUS': "4",
'HF_API_TOKEN': ''
}
Also, you will need to run a bigger instance like a ml.g4dn.12xlarge