This project presents a fine-tuned version of Microsoft's Phi-3.5 model, optimized for enhanced conversational abilities and general knowledge tasks.
Model Details - Base model: microsoft/Phi-3.5-mini-instruct - Fine-tuning method: PEFT (Parameter-Efficient Fine-Tuning) - Training data: [Brief description of your dataset]
Features - Improved response generation for a wide range of topics - Enhanced context understanding and coherence - Optimized for deployment on Hugging Face Spaces
Usage This model can be used for various natural language processing tasks, including: - General conversation - Question answering - Task instructions - Creative writing
Limitations While this fine-tuned model shows improved performance, users should be aware of potential biases and limitations inherent in language models. Always critically evaluate the model's outputs.
Feedback I welcome any feedback, suggestions, or questions about this project. Feel free to open an issue or contribute to further improvements!
Excited to share my new Gradio app featuring the impressive Llama-3.1-Storm-8B model! This app demonstrates the capabilities of Llama-3.1-Storm-8B, an 8B parameter language model created by Ashvini Kumar Jindal, Pawan Kumar Rajpoot, Ankur Parikh,@akjindal53244 Key highlights of Llama-3.1-Storm-8B:
Outperforms Llama-3.1-8B-Instruct on multiple benchmarks:
Instruction Following (IFEval): +3.93% Knowledge-driven QA (GPQA): +7.21% Reduced Hallucinations (TruthfulQA): +9% Function Calling (BFCL): +7.92%
Achieves impressive results with only 8B parameters Uses innovative techniques like self-curation and model merging
Kudos to the creators for pushing the boundaries of smaller language models! This work makes advanced AI more accessible and efficient. #AI #NLP #MachineLearning #GradioApp #Llama3
This model essentially explores having different experts (MoE) for image encoder part of vision language model. How? ๐ง The authors concatenate the vision encoder output tokens together, and they apply "pre-alignment" essentially fine-tune experts with frozen text encoder.
Then they freeze both experts and the decoder and just train the projection layer, and finally, they unfreeze everything for supervised fine-tuning โจ
In the paper, they explore different fusion strategies and vision encoders, extending basic CLIP encoder, and figure out simply concatenating visual tokens works well. Rest of the architecture is quite similar to LLaVA. (see below the architecture)
Excited to share my new Gradio app featuring the impressive Llama-3.1-Storm-8B model! This app demonstrates the capabilities of Llama-3.1-Storm-8B, an 8B parameter language model created by Ashvini Kumar Jindal, Pawan Kumar Rajpoot, Ankur Parikh,@akjindal53244 Key highlights of Llama-3.1-Storm-8B:
Outperforms Llama-3.1-8B-Instruct on multiple benchmarks:
Instruction Following (IFEval): +3.93% Knowledge-driven QA (GPQA): +7.21% Reduced Hallucinations (TruthfulQA): +9% Function Calling (BFCL): +7.92%
Achieves impressive results with only 8B parameters Uses innovative techniques like self-curation and model merging
Kudos to the creators for pushing the boundaries of smaller language models! This work makes advanced AI more accessible and efficient. #AI #NLP #MachineLearning #GradioApp #Llama3
๐ฃ New Project Alert: Phi 3.5 Multimodal AI Demo ๐ Excited to share my latest project that combines the power of Phi 3.5 text and vision models with text-to-speech capabilities! ๐ Key Features: 1๏ธโฃ Phi 3.5 Text Model for dynamic conversations 2๏ธโฃ Phi 3.5 Vision Model for advanced image analysis 3๏ธโฃ Text-to-Speech integration for an audio dimension ๐ ๏ธ Tech Stack:
This project demonstrates the potential of integrating multiple AI models to create a more comprehensive and interactive user experience. It's a step towards more natural and versatile AI assistants. ๐ Check out the demo and let me know your thoughts! How would you extend this project? ๐ Demo Link: sagar007/Multimodal_App #MultimodalAI #PhiModel #MachineLearning #AIDemo
๐ AI Math Equation Solver: Your Step-by-Step Solution Companion
Hello Hugging Face community! ๐ I'm excited to share my latest Space: the AI Math Equation Solver!
๐ What does it do?
This Space uses the power of AI to solve math problems from images. Simply upload a picture of a math equation or problem, and the AI will provide a detailed, step-by-step solution. It's perfect for students, teachers, or anyone looking to understand complex mathematical concepts better.
๐ง How does it work?
- Backend: Utilizes the microsoft/Phi-3.5-vision-instruct model for image understanding and mathematical reasoning. - Frontend: Built with Gradio for a clean, user-friendly interface. - Features: - Image upload for math problems - Detailed step-by-step solutions - Example problems to try instantly
Visit the Space here: [Insert your Hugging Face Space URL]
๐ก Use cases:
- Students: Check your work or get help with homework - Teachers: Create detailed solution guides quickly - Tutors: Explain complex problems more effectively - Self-learners: Understand new mathematical concepts
This is an open project, and I welcome contributions! Whether it's improving the model, enhancing the UI, or adding new features, feel free to fork the project and submit your pull requests.
๐ฃ Feedback:
I'd love to hear your thoughts! How are you using this Space? Any suggestions for improvements? Let me know in the comments below.
๐ Enchanted Tales Generator: A GPT-2 Inspired Story Weaver ๐
Hello Hugging Face community! I'm excited to share my latest project, the Enchanted Tales Generator, inspired by Andrej Karpathy's enlightening YouTube videos on GPT-2.
๐งโโ๏ธ What is the Enchanted Tales Generator?
The Enchanted Tales Generator is a magical text generation app that weaves whimsical stories based on your prompts. It's powered by a fine-tuned GPT model and brings the wonder of AI-generated storytelling to your fingertips.
๐ฅ Inspiration
This project was born from the inspiration I drew from Andrej Karpathy's incredible YouTube series on GPT-2. His clear explanations and deep insights into the workings of language models sparked my imagination and drove me to create something that could bring joy and creativity to others.
๐ฎ Features
- Story Incantation: Input your magical prompt to start your tale - Scroll Length: Adjust the length of your generated story - Magical Intensity: Control the creativity (temperature) of the generation - Arcane Diversity: Fine-tune the variety of word choices (top-k sampling)
You can experience the Enchanted Tales Generator right here on Hugging Face Spaces: [Insert your Spaces link here]
๐ ๏ธ Behind the Scenes
The app is built using: - PyTorch for the underlying GPT model - Gradio for the user interface - Hugging Face Spaces for deployment
I've implemented techniques learned from Karpathy's videos, such as: - Custom GPT architecture - Top-k sampling for diverse outputs - Temperature-controlled generation
๐ Future Enchantments
I'm continuously working on improving the Enchanted Tales Generator. Some ideas for future updates include: - Fine-tuning on specific genres of stories - Adding options for character and setting generation - Implementing more advanced sampling techniques