finetuning

Someone open-sourced the KRONOS model, which treats each candlestick as a token to predict the next candle (pre-trained on 12 billion candlesticks). It can be integrated 100% free into Claude Code and TradingView to build a full AI crypto trading and prediction system.

NVIDIA's Nemotron 3.5 Super VL is now available on the River API for inference, finetuning, and RL, with claims that it outperforms Kimi K2.6 on text-to-SQL evaluations even before training and can be trained to beat Astra and Opus 5.5.

A research project that fine-tunes the Aria piano transformer on twelve jazz pianists using gated cross-attention conditioning on learned pianist embeddings, achieving 70% intended-pianist attribution on generated continuations versus 37% without conditioning. The work, inspired by Dick Hyman's 'In the Styles of… The Great Jazz Pianists', is presented at ISMIR 2026 in Abu Dhabi.

社区成员持续在本地 3 张 32GB V100 上从头后训练 Yandex ALiceAI-80B-A3B，通过 Qwen 3.8 27B 的浅层蒸馏传授链式思维与对话能力；第一轮 SFT 已完成但严重欠拟合，正在扩大合成指令数据量并以更广的数据分布进行第二轮训练，同时开源了其离轨蒸馏引擎 sftmill。

The article benchmarks the Qwen3.6-35B-A3B base model and five finetunes, finding that only Occamy-1.0 is competitive with the base model, while others like Tiel underperform significantly.

The tweet discusses when and how to finetune a specialized classifier model that is better than Opus, faster than Jev, and runs on user devices.

Maxime Rivest demonstrates creating a motion graphic video using Claude's Opus model in a single prompt, enhancing accessibility for explaining AI finetuning work, and discusses finetuning specialized decision models.

The article explains when and how to finetune a specialized decision model classifier that outperforms Opus, is faster than Jev, and runs on user devices.

Hemmingway-1 is a finetuned version of the Qwen3.8-27B AI model, designed to generate text in a more human-like writing style.

Jovan from UkisAI thanks the community for the success of Swift Qwen 3.8 27B, an open-source model that reduces token usage by 58.3% and increases speed by 1.95x through efficient thinking patterns. Future improved checkpoints and models are planned.

The author tests the Muse-glimmer-30b model for creative writing and finds it impressive, outperforming other local models like qwen3.8-27b in emulating writers' styles.

A local web UI for finetuning AI models on personal text, featuring live gradient activity monitoring, A/B prompt comparison, and AMD ROCm compatibility.

The paper introduces Diff Mining, a framework for identifying finetuning objectives in language models by analyzing logit differences between finetuned and base models, enabling interpretable auditing of learned behaviors.

Apodex is an open-sourced deep research harness and AI model, which is a finetune of Qwen 3.5 35B A3B, achieving performance comparable to frontier models with only 3B active parameters.

This blog post introduces how to train and finetune multi-vector embedding models using the Sentence Transformers library, showcasing its v6.0 update with a new MultiVectorEncoder type and demonstrating superior performance on medical retrieval tasks.

This paper investigates whether the Knobe effect (a moral bias in intentionality judgments) emerges in finetuned LLMs, and uses layer-patching analysis to localize the bias to specific layers, showing that targeted interventions can eliminate the effect without retraining.

This paper introduces Enlightenment, a training-free post-tuning method for large-scale models that modifies shortcuts in key modules without weight updates, achieving sudden capability boosts. It demonstrates effectiveness across LLMs and VLMs via attention head-mixing and scalar-modulated residual connections.

A proof-of-concept In-Context LoRA adapter for LTX-Video 2.3 that re-renders video scenes from new camera angles using a fixed vocabulary prompt, trained on synthetic multi-view data.

BLOOMZ and mT0 are multilingual models finetuned on the crosslingual task mixture xP3, enabling zero-shot instruction following in dozens of languages.

This paper introduces Contrastive Decoding Diffing (CDD), a method that recovers verbatim finetuning data from LLMs using only logit access, without requiring model weights or activations. It demonstrates high verbatim recovery across multiple model families and reveals unintended data leakage, such as the recurring fictional persona 'Dr. Elena Rodriguez' from synthetic training data.