This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
srun -l "${ARGS[@]}" python $SOURCE_DIR/merge_peft_checkpoint.py --hf_model_name_or_path $BASE_MODEL_BF16 --peft_adapter_checkpoint_path $ADAPTER_PATH --output_model_path $MERGE_MODEL_PATH --deepseek_v3 true Evaluate the fine-tuned model Use the basic testing scripts provided by DeekSeek to deploy the merged model. py --input-fp8-hf-path./DeepSeek-R1
systemarchitectures) Spatial relationships in maps or layouts A purely text-based approach fails to capture this crucial layer of information. The full working code with UI, modular structure, and search logic is available in the [GitHub repository](github.com/SridharSampath/multimodal-rag-demo).* resize((512, 512)).tobytes().hex()
The following code snippet demonstrates how to call the Amazon Rekognition DetectModerationLabel API to moderate images within an AWS Lambda function using the Python Boto3 library: import boto3 # Initialize the Amazon Rekognition client object rekognition = boto3.client('rekognition') The following diagram illustrates this architecture.
We organize all of the trending information in your field so you don't have to. Join 17,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content