- Bangalore, Karnataka, India
- https://prashantkikani.com
- in/prashant-kikani
Stars
Font files available from Google Fonts, and a public issue tracker for all things Google Fonts
Windows/macOS/Linux binaries and installation methods of TinyTeX
Google Drive Public File Downloader when Curl/Wget Fails
Build AI WhatsApp Bots with Pure Python
Finetune Llama 3.2, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory
A Native-PyTorch Library for LLM Fine-tuning
Uses tokenized query returned by python-sqlparse and generates query metadata
Efficiently Fine-Tune 100+ LLMs in WebUI (ACL 2024)
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
All scripts are in python language to trade in zerodha using algorithms.
Create Custom GPT and add/embed on your site using Assistants api
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
🦜🔗 Build context-aware reasoning applications
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
Examples and guides for using the OpenAI API
Robust Speech Recognition via Large-Scale Weak Supervision
High-Resolution Image Synthesis with Latent Diffusion Models
A latent text-to-image diffusion model
A simple HTML content extractor in Python. Can be run as a wrapper for Mozilla's Readability.js package or in pure-python mode.
mvoelk / ssd_detectors
Forked from rykov8/ssd_kerasSSD-based object and text detection with Keras, SSD, DSOD, TextBoxes, SegLink, TextBoxes++, CRNN
CCP dataset from "Clothing Co-Parsing by Joint Image Segmentation and Labeling " (CVPR 2014)
Open source code for AlphaFold.
HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.