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Have you read the Contributing Guidelines ?
Yes
Description
I have added GenerativeAI projects ;
Bacis Project 1 ( ImagetoTextgenerator): This Python script uses the Hugging Face transformers library to generate image captions with a pre-trained Vision-Encoder-Decoder model (vit-gpt2-image-captioning). It processes images using the ViTImageProcessor, generates captions using the VisionEncoderDecoderModel, and decodes these captions with the AutoTokenizer. The script sets up the model to run on a GPU if available, or otherwise on a CPU, and uses beam search for better caption quality. Finally, it prints the generated caption for the provided image path.
Basic Project 2 ( TexttoImageGenerator):
This Python script leverages the Hugging Face transformers and diffusers libraries to generate images from text prompts using the Stable Diffusion model. It defines a configuration class (CFG) to hold constants and parameters, such as device type (GPU), random seed for reproducibility, model IDs, and image generation settings. The script initializes the Stable Diffusion model and moves it to the GPU. The generate_image function takes a text prompt and generates an image using the specified parameters, resizing it to the desired dimensions. An example usage is provided to generate an image from the prompt "Apple on a tree".
Intermidiate Project 1 (MultiLingualTextToImageGenerator):
The script translates from any text to English and generates an image from the translated prompt using Stable Diffusion
Advance Project 1 ( Langchain based Chat Retrival Chatbot)
This script creates a Streamlit app that uses LangChain components to provide conversational insights about Mumbai properties.
Fixes #985
Checklist
README.md
and link to my code.Related Issues or Pull Requests
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