ModelScope Finetuning supports machine learning models, deployment, inspection, datasets, or AI development workflows.
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Cloud native AI, analytic and data management platform that supports the analytics life cycle.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Generative AI Resources for Berkeley Law Faculty & Staff - Berkeley Law provides machine-learning models, research, training resources, or…
LLM Resources Hub provides machine-learning models, research, training resources, or evaluation tools.
ACE-Step 1.5 supports machine learning models, deployment, inspection, datasets, or AI development workflows.
AI Jukebox supports machine learning models, deployment, inspection, datasets, or AI development workflows.
A comprehensive set of fairness metrics for datasets and machine learning models.
Easy way to turn any app into searchable data for LLMs.
Code and documentation to train Stanford's Alpaca models, and generate the data.
Ambrosia helps you clean up your LLM datasets using other LLMs.
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.
Platform for Production Data Science.
One API key, 63 AI agent tools: web search, scraping, AI generation, OCR, crypto data. LangChain + MCP ready. Pay per call with credits or x402/USDC.
Machine Learning and Data Mining for Astronomy.
Automated machine learning for image, text, tabular, time-series, and multi-modal data.
AI Native database for embedding vectors.
Curated list of Turkish AI models, datasets, papers.
Helps find, analyze or synthesize information for research and knowledge discovery.
Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
An easy-to-use feature store. Optimized for time-series data.
CLIP Interrogator supports machine learning models, deployment, inspection, datasets, or AI development workflows.
A curated list of language modeling researches for code and related datasets.
Track your datasets, code changes, experimentation history, and models.