CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
Optimize prompts, code, and more with AI-powered Reflective Optimization
- agent-skills
- coding-agent
- discovery
- distributed-evolutionary-algorithms
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
- chinese
- computer-vision
- multi-modal-learning
- nlp
Easily compute clip embeddings and build a clip retrieval system with them
- semantic-search
- deep-learning
- multimodal
- ai
Doing simple retrieval from LLM models at various context lengths to measure accuracy
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
- deep-learning
- evaluation
- foundation-models
- instruction-following
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
- aifinance
- fintech
- llama
- machine-learning
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell