Original (English): [00:00.000 –> 00:15.860]I want to thank the organizers for choosing a paper for this award. It was very nice. And I also want to thank my incredible co-authors and collaborators, Oriol Vinyals and Quoc Le, who stood right before you a moment ago. And what you have here is an image, a screenshot, from a similar talk 10 years ago at NeurIPS in 2014 in Montreal. It was a much more innocent time. [00:15.860 –> 00:35.980]Here we are, shown in the photos. This is the before. Here’s the after, by the way. And now we’ve got my experienced, […]
New Chameleon AI Model: Chameleon-Code_Explation_Gemma29b-v2
I am excited to introduce my new Chameleon AI model – Chameleon-Code_Explation_Gemma29b-v2! This model has been specifically developed to understand and explain the classes of the Chameleon CMS system and is optimized for efficient inference using 4-bit quantization. This makes the use of the model even more resource-efficient and faster. What is the Chameleon-Code_Explation_Gemma29b-v2 Model? Chameleon-Code_Explation_Gemma29b-v2 is a fine-tuned version of the Unsloth Gemma model and is based on a transformer-based language model. It has been trained to explain the structure and components of the Chameleon CMS system. The Chameleon CMS is a combination of shop software and content management […]
Accelerating Model Training with Unsloth: My Chameleon CMS AI Journey
In the rapidly evolving world of AI, staying ahead with cutting-edge tools and techniques is vital. Recently, I completed a successful model training session with Unsloth, a library designed for faster, more efficient model fine-tuning. My goal was to enhance the understanding and generation of PHP class explanations within the Chameleon CMS framework using the Gemma-2-9b model. Here’s a step-by-step recount of how I leveraged Unsloth to achieve fast, accurate results while keeping memory usage optimal Setting Up Unsloth for Model Fine-Tuning I began by installing the necessary packages for Unsloth and Flash Attention 2, a library crucial for softcapping […]
Building a Product Search System with Sentence Embeddings and Similarity Scoring
We will explore how to build a product search system that leverages sentence embeddings and similartiy scoring to improve search relevance. For this projekt, we need a lightweight model from “sentence-tansformers” library. Wyh: Because we need per Product Vector Space, that must be fast and stabil. I Founded this “all-MiniLM-L6-v2” model, is small, efficient and maps sentences to 384-dimensional dense vector space, making it suitable for tasks like semantic search. Let’s Start, Step 1: Setting Up the Envrioment: First, install the necessary library: Then, import the required modules and load the model: Step 2: Generation Embeddings: We will generate embeddings […]
AI Model Trainer with EleutherAI/gpt-j-6b for Chameleon Shop Codes
The Trainer use actually the best chatgpt alternative model on huggingface. Here is the Training notice from Original Source: This model was trained for 402 billion tokens over 383,500 steps on TPU v3-256 pod. It was trained as an autoregressive language model, using cross-entropy loss to maximize the likelihood of predicting the next token correctly. https://huggingface.co/EleutherAI/gpt-j-6b#training-procedure Dataset Links: https://d8devs.com/chameleon-base-and-chameleon-shop-datasets-20230530-1918/ Views: 61