How to Fine-Tune LFM2 Using QLoRA and DPO: A Complete Step-by-Step Coding Tutorial on Google Colab
In this tutorial, we fine-tune Liquid AI’s LFM2 model through a complete open-source workflow. We start by loading the base LFM2 checkpoint with QLoRA, preparing a chat-style supervised fine-tuning dataset,…
TinyFish Launches BigSet: An Open-Source Multi-Agent System That Builds Structured Live Datasets from Plain-English Descriptions
Building a structured dataset from the web is still a pipeline problem. You identify a data source, write or configure a scraper, design a schema, handle deduplication, schedule refreshes, and…
Alibaba’s Qwen Team Launches Qwen3.7-Plus, Adding Vision, Deep Reasoning, Tool Invocation, and Autonomous Iteration on the Bailian Platform
Alibaba’s Qwen team has released Qwen3.7-Plus. The model is now available through Alibaba Cloud’s Bailian platform. Bailian is the console international users access as Model Studio. It offers API services…
JetBrains Releases Mellum2: A 12B MoE Model for Fast, Specialized Tasks in Multi-Model AI Pipelines
JetBrains released Mellum2, open-sourcing the weights under the Apache 2.0 license. The first version of Mellum was a completion-focused 4B dense model. Mellum2 is its successor: a general-purpose model specialized…
How to Speed Up Transformer Training Using NVIDIA Apex (FusedAdam, FusedLayerNorm) and Native torch.amp
print(“\n### SECTION D: end-to-end Transformer (vanilla fp32 vs Apex fused + AMP) ###”) VOCAB, D, NHEAD, LAYERS, SEQ, BATCH, STEPS = 2000, 256, 4, 4, 128, 32, 60 class Block(torch.nn.Module):…
MiniMax Releases MiniMax M3 with MSA Architecture Supporting 1M-Token Context, Native Multimodality, and Agentic Coding
MiniMax officially released MiniMax M3 on June 1, 2026. The model introduces MSA (MiniMax Sparse Attention), a new sparse attention architecture that gives M3 a 1M-token context window. M3 also…
Meet Memory OS: A 6-Layer Open-Source Memory Stack Built on Top of Hermes Agent
Hermes Agent already remembers across sessions. The open-source agent from Nous Research ships with curated memory files and full-text session search. But a new community project argues that built-in memory…
Parallax: A Parameterized Local Linear Attention That Keeps Softmax and Adds a Learned Covariance Correction Branch
The Transformer’s attention mechanism has barely changed since 2017. Most efficiency work has tried to replace softmax attention outright. A new paper takes a different route. It keeps softmax attention…
An Implementation of the Microsoft Agent Governance Toolkit for Safe AI Agent Tool Use with Policies, Approvals, Audit Logs, and Risk Controls
scenarios = [ { “name”: “Safe database read”, “tool”: research_db, “kwargs”: { “table”: “customers”, “operation”: “select”, “type”: “select”, “sensitivity”: “medium” } }, { “name”: “Blocked destructive database action”, “tool”: research_db,…
A Coding Implementation on Loguru for Designing Robust, Structured, Concurrent, and Production-Ready Python Logging Pipelines
banner(“1) logger.configure(): handlers + custom level + extra + patcher”) mem = MemorySink() logger.configure( handlers=[ {“sink”: sys.stderr, “format”: console_formatter, “level”: “DEBUG”, “colorize”: True, “backtrace”: True, “diagnose”: True}, {“sink”: mem, “level”:…









