AI IPO Analyst Automates Indian IPO document analysis by transforming complex financial documents into structured reports with real-time market data, financial ratios, and automated processing. Check out this powerful financial analysis tool https://
github.com/AKMessi/AI-IPO
-Analyst
…
OPEN SOURCE
-

AI IPO Analyst: Automated Indian IPO Document Analysis Tool
By
–
-
Hugging Face releases AI sheets for dataset building without code
By
–
Hugging Face just dropped AI sheets to build and enrich datasets without writing a single line of code.
— Shubham Saboo (@Saboo_Shubham_) 16 août 2025
Works with Qwen, Kimi, Llama 3 and other opensource LLMs.
100% Free, local and Opensource.pic.twitter.com/onvrgg5hqRHugging Face just dropped AI sheets to build and enrich datasets without writing a single line of code. Works with Qwen, Kimi, Llama 3 and other opensource LLMs. 100% Free, local and Opensource.
-
Axolotl: YAML-based LLM fine-tuning and LoRA optimization framework
By
–
4. Axolotl • Yaml-based setup for fine-tuning, LoRA/QLoRA, DPO, GRPO, and multimodal workflows
• Includes kernel optimizations for memory-efficient training GitHub repo: -
DeepSpeed: Distributed Fine-Tuning Framework for Large Language Models
By
–
3. DeepSpeed • Built for large-scale distributed fine-tuning with ZeRO and FSDP
• Optimized for multi-GPU and multi-node training with advanced memory management
• Trusted in production environments for scalable LLM training GitHub repo: -
LLaMA Factory: Fine-tune 100+ Models with Simple CLI
By
–
2. LLaMA Factory • Fine-tune over 100 models (LLaMA, Mistral, Gemma, etc.) using a simple CLI or WebUI
• Supports LoRA, QLoRA, full or frozen fine-tuning across 2–8‑bit precision GitHub repo: -
Unsloth AI: Fast LLM Fine-tuning with 70% Less VRAM
By
–
1. Unsloth AI • Fine-tune models like Qwen3, Llama 4, and Gemma 3 up to 2× faster with 70% less VRAM
• Supports low-resource setups and runs on consumer GPUs or even Colab/Kaggle with ~3 GB VRAM GitHub repo: -
Four Open Source Libraries Accelerate LLM Fine-tuning
By
–
Fine-tuning massive LLMs used to be painfully slow, but not anymore! Here are 4 libraries that accelerates fine-tuning of Large Language Models 100% Open Source
-
Gemma 3 270M: Efficient Open Model for Edge Devices
By
–
New hyper-efficient addition to our amazing Gemma open models: Gemma 3 270M packs a real punch for its tiny size! It’s super compact and power efficient, so you can easily run your own task-specific fine-tuned systems on edge devices. Enjoy building with it!
-
AI Stack Fundamentals Need Major Improvements Across All Layers
By
–
Every part of the AI stack – semiconductors, GPUs, Python, PyTorch, LLMs, post-training, etc. – is in major need of improvement.
-
GPT-OSS demonstrates impressive safety maximization features
By
–
Ohh nice to see how safemaxxed gpt-oss is!