-
Rakuten Inc.
- Tokyo, Japan
- https://avinash-mishra.github.io/my-portfolio
- in/avinash-mishra-a0846360
Highlights
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Starred repositories
Official Repo for Open-Reasoner-Zero
Code examples showing how to use Gemini, Gemma, Imagen, and more.
Achieve the llama3 inference step-by-step, grasp the core concepts, master the process derivation, implement the code.
An overview of GRPO & DeepSeek-R1 Training with Open Source GRPO Model Fine Tuning
Educational implementation of a small GPT model from scratch in a single Jupyter Notebook
Optimized Large Language Models for Financial Applications – Efficient, Scalable, and Domain-Specific AI for Finance.
Building applications with DeepSeek R1 model
Building DeepSeek R1 from Scratch
AI Agent Work shop include Agent from Corepython, using CrewAI and Using SmolAgent
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
This repository contains the Hugging Face Agents Course.
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
ChatGPT Jailbreaks, GPT Assistants Prompt Leaks, GPTs Prompt Injection, LLM Prompt Security, Super Prompts, Prompt Hack, Prompt Security, Ai Prompt Engineering, Adversarial Machine Learning.
Anthropic's Interactive Prompt Engineering Tutorial
An open-source alternative to OpenAI and Gemini's deep research.
Learn AI/ML for beginners with a roadmap and free resources.
Video Generation Foundation Models: https://saiyan-world.github.io/goku/
Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS …
vLLM’s reference system for K8S-native cluster-wide deployment with community-driven performance optimization
Podman: A tool for managing OCI containers and pods.
save 200 a month and use deep research right in your terminal. - port of https://github.com/dzhng/deep-research but in python
Developing powerful AI assistants and agents using Genesis and Agentic-RAG.