Trained on billions of lines of public code, GitHub Copilot puts the knowledge you need at your fingertips, saving you time and helping you stay focused.
It definitely increases my productivity.
Based on our record, GitHub Copilot seems to be a lot more popular than MiniGPT-4. While we know about 302 links to GitHub Copilot, we've tracked only 8 mentions of MiniGPT-4. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
To put these points in context, consider how shell agents stack up against AI assistants built into IDEs (such as GitHub Copilot or Replit’s Ghostwriter). IDE agents shine when you want inline code suggestions as you type or tight integration with a particular editor. They offer intuitive GUI support for code completion, debugging panes, and visual diff tools. However, they come with trade‑offs. - Source: dev.to / about 18 hours ago
Enter GitHub Copilot. Originally launched as an AI-powered autocomplete tool, Copilot quickly gained traction among developers. It helped write boilerplate code, offered smart suggestions, and reduced context-switching. But now, it has evolved into something more powerful: the GitHub Copilot Coding Agent. - Source: dev.to / 1 day ago
Writing comprehensive unit and integration tests is one of the best ways to ensure code quality – but it’s also labor-intensive. AI can help automate this tedious task. New AI assistants (like GitHub Copilot) can analyze Python functions and automatically generate meaningful test cases. As one developer puts it, “progress in AI has opened doors to automated test generation…presenting developers with an innovative... - Source: dev.to / 2 days ago
Tools like GitHub Copilot, Replit Ghostwriter, and Tabnine don’t just suggest code, they write it. These models are trained on billions of lines of open-source code and can auto-generate:. - Source: dev.to / 8 days ago
Or tools like GitHub Copilot, which autocomplete not just functions but full app logic. These aren’t just helping developers. They’re starting to think like one. - Source: dev.to / 8 days ago
Isn't there only two open multimodal LLMs, LLaVA and mini-gpt4? Source: almost 2 years ago
So we use MiniGPT-4 for image parsing, and yep it does return a pretty detailed (albeit not always accurate) description of the photo. You can actually play around with it on Huggingface here. Source: about 2 years ago
We use MiniGPT-4 first to interpret the image and then pass the results onto GPT-4. Hopefully, once GPT-4 makes its multi-modal functionality available, we can do it all in one request. Source: about 2 years ago
But I would like to bring up that there are some multi models(llava, miniGPT-4) that are built based on censored llama based models like vicuna. I tried several multi modal models like llava, minigpt4 and blip2. Llava has very good captioning and question answering abilities and it is also much faster than the others(basically real time), though it has some hallucination issue. Source: about 2 years ago
Https://minigpt-4.github.io/ <-- free image recognition, although not powered by true GPT-4. Source: about 2 years ago
Tabnine - TabNine is the all-language autocompleter. We use deep learning to help you write code faster.
Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.
Codeium - Free AI-powered code completion for *everyone*, *everywhere*
LangChain - Framework for building applications with LLMs through composability
Cursor - The AI-first Code Editor. Build software faster in an editor designed for pair-programming with AI.
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.