ParagEkbote/efficient-model-serving
Deploy AI models with an API through quantization and containerization.
ML Engineer | Python | Research → Production Deployment | 1 year supporting tech startups | Passionate OSS Individual Contributor | Technical Reviewer
Repositories
ParagEkbote/hf-genomic-dataset-enrichment
A Dagster-orchestrated Data Enrichment Pipeline that transforms genomic sequences from the Carbon pretraining corpus into structured and vector-search-ready datasets, combining biological metadata with model-derived features.
ParagEkbote/contributions.md
Changelog of Open Source Contributions
ParagEkbote/awesome-hf-playbooks
Awesome HF Playbooks is a curated collection of advanced guides and resources for practitioners working with Hugging Face and large-scale machine learning.
ParagEkbote/ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
ParagEkbote/feast
The Open Source Feature Store for AI/ML
ParagEkbote/great_expectations
Always know what to expect from your data.
ParagEkbote/ParagEkbote
About Me.
ParagEkbote/flyte-sdk
Type-safe, distributed orchestration of agents, ML pipelines, and real-time inference — in pure Python with async/await.
ParagEkbote/LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
ParagEkbote/ROLL
An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models
ParagEkbote/zenml
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
ParagEkbote/community-integrations
Community supported integrations for the Dagster platform.
ParagEkbote/model-kernels
ParagEkbote/pruna-cookbook
ParagEkbote/optunahub-registry
The registry of the OptunaHub packages
ParagEkbote/dagster
An orchestration platform for the development, production, and observation of data assets.
ParagEkbote/VeOmni
VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo
ParagEkbote/pruna
Pruna is a model optimization framework built for developers, enabling you to deliver faster, more efficient models with minimal overhead.
ParagEkbote/pixel-art-bench
ParagEkbote/Liger-Kernel
Efficient Triton Kernels for LLM Training
ParagEkbote/RL
Scalable toolkit for efficient model reinforcement
ParagEkbote/bedrock-agents-mcp-workshop
Hands-on Workshop on Building AI Agents with Strands, MCP, and Temporal
ParagEkbote/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
ParagEkbote/optuna-integration
Extended functionalities for Optuna in combination with third-party libraries.
ParagEkbote/optuna
A hyperparameter optimization framework
ParagEkbote/optuna-examples
Examples for https://github.com/optuna/optuna
ParagEkbote/hf-model-inspector
A package and gh-action to generate quality reports on Hugging Face model stats and usage, addressing ambiguity in open model releases.
ParagEkbote/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
ParagEkbote/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.