Brief

A developer has created a method to run a 35 billion parameter multimodal LLM on free Kaggle GPUs, overcoming the typical limitations of such platforms. The solution involves using Qwen3.6-35B-A3B quantized to 4-bit, hosted on Kaggle's T4 GPUs for up to 12 hours per session. It leverages llama.cpp for inference and an OpenAI-compatible API, with Cloudflare Quick Tunnel providing a stable public URL that supports token streaming, unlike other free tunneling services. AI

This article explores how the ONNX framework can accelerate inference times for Sentence-BERT (SBERT) models, which are commonly used for generating sentence embeddings. The author demonstrates this by converting the `all-MiniLM-L6-v2` SBERT model to ONNX format and comparing its inference speed against the vanilla model on both CPU and GPU using a dataset of 1000 movie descriptions from Kaggle. The post provides installation instructions for ONNX and related libraries, and outlines the experimental setup for measuring performance. AI

A developer built Sakhi, a Hindi voice-to-form application for India's community health workers, in six weeks. The system addresses challenges with unreliable cloud speech-to-text and intermittent connectivity in rural areas. Sakhi offers two modes: a workstation setup using Whisper and Gemma for voice transcription and data extraction, and an offline on-device mode on Android for text-based form filling and danger sign detection. AI

This tutorial demonstrates how to build and evaluate an Alzheimer's MRI classification pipeline using PyTorch's ResNet18 model. It highlights the common pitfall of models achieving high accuracy by exploiting dataset-specific artifacts rather than genuine medical features. The guide emphasizes the importance of using techniques like Grad-CAM to visualize model attention and ensure it's focusing on relevant anatomical regions before clinical deployment. AI