WebLlama

Construct powerful agents capable of browsing the web and conversing with you based on instructions

PremiumNewProductProgrammingWeb NavigationDialogue Agent

WebLlama is an agent fine-tuned for web navigation and dialogue built on Meta Llama 3. It aims to build user-centered agents that assist with web browsing, rather than replace users. The model outperforms GPT-4V (zero-shot) by 18% on the WebLINX benchmark, demonstrating its exceptional performance in web navigation tasks.

Train web navigation tasks using Meta Llama 3
Fine-tune on the WebLINX dataset containing over 24K instances of web interactions
Provide training scripts
optimization configurations
and guidance on training state-of-the-art Llamas
Integrate with existing deployment platforms such as Playwright
Selenium
and BrowserGym
Offer models and training evaluation data on Hugging Face Model Hub
Train and evaluate on the basis of 150 websites

Researchers and developers: Utilize WebLlama for research and development on web navigation tasks
Corporate users: Automate web interactions with WebLlama to enhance work efficiency
Technology enthusiasts: Explore and learn about the latest web navigation and dialogue agent technologies

Automatize online booking processes using WebLlama
Integrate into existing systems to perform complex web data extraction tasks
As a research tool
explore new methods for web navigation and dialogue systems

Step 1: Access the WebLlama GitHub page to obtain the model and training scripts
Step 2: Set up and configure the model locally according to the provided guidelines
Step 3: Train and fine-tune the model using the WebLINX dataset
Step 4: Deploy the trained model to the desired platform or service
Step 5: Interact with the WebLlama agent through dialogue or instructions to complete specific web navigation tasks

Visit

WebLlama Visit Over Time

Monthly Visits

1058

Bounce Rate

41.84%

Page per Visit

1.0

Visit Duration

00:00:00

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