Heykuki News
Top
New
Best
Ask
Show
Jobs
Toggle theme
Login
Top
New
Best
Ask
Show
Jobs
451.
▲
Train an LLM from Scratch in a Single Python Notebook
(github.com/kevinpdev)
3 points
kevinpdev
a year ago
discuss
452.
▲
Elixir Bumblebee: Pre-Trained Neural Network Models in Axon
(github.com/elixir-nx)
3 points
tosh
a year ago
discuss
453.
▲
Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget
(github.com/SonyResearch)
3 points
tylergem
a year ago
discuss
454.
▲
Show HN: Lego Meets AI: BricksRL to train your own Lego robot
(bricksrl.github.io)
3 points
vmoens
2 years ago
discuss
455.
▲
Show HN: NviWatch – Lightweight GPU Monitoring for AI/ML Training
(github.com/msminhas93)
3 points
msminhas
2 years ago
discuss
456.
▲
Show HN: IsThereNet, a macOS app for stress-free working on train rides
(github.com/FuzzyIdeas)
3 points
alin23
2 years ago
discuss
457.
▲
AI Voice Agents: Opensource, Pre-Trained Voice Activity Detector
(github.com/snakers4)
3 points
selvan
2 years ago
discuss
458.
▲
Train and host a free chatbot clone of yourself online
(gist.github.com)
3 points
todsacerdoti
2 years ago
discuss
459.
▲
Effective Training of Diffusion Model for Photorealistic Text-to-Image Synthesis
(github.com/Kwai-Kolors)
3 points
lnyan
2 years ago
discuss
460.
▲
Show HN: Flaim – pre-trained vision backbones for Flax
(github.com/BobMcDear)
3 points
bornaahz
2 years ago
discuss
461.
▲
RNNoise 0.2 – now trained using only publicly available CC-licensed datasets
(github.com/xiph)
3 points
pabs3
2 years ago
discuss
462.
▲
Show HN: workin – A web app to create and run smart trainer workouts
(github.com/jsmolka)
3 points
jsmolka
2 years ago
discuss
463.
▲
Training and inference code for audio generation models
(github.com/Stability-AI)
3 points
treesciencebot
3 years ago
discuss
464.
▲
Show HN: Every Breath You Take – Heart Rate Variability Training
(github.com/kbre93)
3 points
kbre93
3 years ago
discuss
465.
▲
An open platform for training, serving, and evaluating large language models
(github.com/lm-sys)
3 points
udev4096
3 years ago
discuss
466.
▲
Show HN: This project allows you to easily implement parallel training
(github.com/NoteDancing)
3 points
NoteDancing
3 years ago
discuss
467.
▲
Train Your Own Vicuna on Llama-2
(github.com/skypilot-org)
3 points
zhwu
3 years ago
discuss
468.
▲
Show HN: Train language-models on your GPU with pure Rust
(github.com/keyvank)
3 points
keyvank
3 years ago
discuss
469.
▲
Show HN: Train Your Own Language Model on Your Favourite Programming Language
(github.com/rojas-diego)
3 points
rojasdiego
3 years ago
discuss
470.
▲
Microsoft bioGPT: pre-trained transformer for biomedical text
(github.com/microsoft)
3 points
matco11
3 years ago
discuss
471.
▲
Local working implementations of distributed ML model training
(github.com/hundredblocks)
3 points
e_ameisen
3 years ago
discuss
472.
▲
Cramming the training of a (BERT-type) language model into limited compute
(github.com/JonasGeiping)
3 points
homarp
3 years ago
discuss
473.
▲
Show HN: A Go package to train and classify bogus text, usernames and emails
(github.com/prophittcorey)
3 points
c-p
3 years ago
discuss
474.
▲
Ailia-models: A collection of pre-trained, state-of-the-art AI models
(github.com/axinc-ai)
3 points
mmmmkay
4 years ago
discuss
475.
▲
ControlFlag – flag anomalous source code by learning from training data
(github.com/IntelLabs)
3 points
pabs3
4 years ago
discuss
476.
▲
Train ML Models 2-4x Faster with SOTA Research
(github.com/mosaicml)
3 points
averylamp
4 years ago
discuss
477.
▲
Show HN: Train an AI model on Android without coding, make your own app with it
(github.com/OutSorcerer)
3 points
OutSorcerer
4 years ago
discuss
478.
▲
Large-Scale Self-Supervised Pre-Training Across Tasks, Languages, and Modalities
(github.com/microsoft)
3 points
axiomdata316
4 years ago
discuss
479.
▲
Txtai 3.3 released – Export and work with ONNX models, train QA models
(github.com/neuml)
3 points
dmezzetti
5 years ago
discuss
480.
▲
HuggingPics: Easily train and deploy image classifiers for anything
(github.com/nateraw)
3 points
julien_c
5 years ago
discuss
More