Using beautiful Grafana dashboards for everything internally, so much nicer than Tensorboard. Wandb still good but doesn't really work with decentralised training. Makes me wonder what the internal vis tooling is like in openai - must be incredible.

Genesis-Embodied-AI で全長40cmの小型ヒューマノイドを歩行させる強化学習の過程をレンダリングしながら確認できました. 最初は揺れるだけですが、最終的に歩行できてます（倍速動画）. 右側の Tensorboard で Reward の変化をみるために定期的にリロードしています. #GENESIS

reading tensorboard logs the way God intended

Peeking at tensorboard after 7 hours of training . (it hasn’t learned shit)

Happy to announce the PySR v1.0 release!. PySR lets you do high-performance symbolic regression from Python. New:.You can learn multiple symbolic expressions simultaneously. Also:. Parametric expressions. TensorBoard support. Improved search. Julia-based inference

tensorboard is actually fun!

Paperspace上でComfyUIを実行するのにようやっと成功した　なぜかtensorboardのリンクが生成されなくて困ってた…. そしてNAID GeneratorでComfyUIからNAIを実行するのに成功 APIキーを入力した.envを作成するのが一番たいへんだった…　やったことはリプ欄以下.#ComfyUI #NovelAI

【✨Stable DiffusionのLoRA学習「Tensorboard」で最高のモデルを見つける秘訣とは？！】. AI画像生成のStable Diffusionで、LoRAモデルのトレーニングに役立つ「Tensorboard」について解説します！LoRA学習は奥が深いんです😲

Huggingface's trackio is what I expected wandb to be: a healthy alternative to the tensorboard with a transparent sharing system .

When that first audio sample in your tensorboard slaps 🎵

Just gave @LightningAI Studio platform a whirl for my ML models – absolutely blown away! 🚀 Seamless GPU selection, auto-scaling, and built-in support for VS Code, Jupyter, TensorBoard, and more. It's a game-changer for ML development!

TensorBoard、なんやかんやで動きました….情報いただいた方々ありがとうございます(_ _)

i like tensorboard, i have no idea what any of this means but it looks cool

RF-DETR 1.1.0 release. - early stopping.- gradient checkpointing.- resume training.- saving metrics, TensorBoard and W&B logging. expect 3× smaller checkpoints, 20% faster training, and YOLO dataset support in the next release. link:

remember to lock in and track key metrics to drive actionable business results . You can also ask Claude to log everything to tensorboard and then run.tensorboard serve --logdir logs. code:.from torch.utils.tensorboard import SummaryWriter.tb_writer =

可愛いメイドさんがComfyUIをpaperspaceで使う時のurl変換をお届けします. sed -i 's@logging.info(\"To see the GUI go to: {}://{}:{}\".format(scheme, address_print, port))@print(\" https://tensorboard-\"+os.environ.get(\"PAPERSPACE_FQDN\"))@' /notebooks/ComfyUI/server.py

TensorBoardやWandBでは大袈裟だなってケース用にインラインでリアルタイム学習進捗を表示するcode snippet書きました。. / Google Colab+PyTorch Lightningの学習進捗をMatplotlibでリアルタイム可視化する方法

Why does everyone use Grafana if TensorBoard exists

Try using @rerundotio for robot learning! Plotting training/validation loss is just as easy as wandb/tensorboard. But it really shines if you have an evaluation visualization that standard tools can't handle, like visualizing policy rollouts! EX: diffusing trajectories.