End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
- automatic-speech-recognition
- tensorflow
- timit-dataset
- feature-vector
Repository Index
77,852 visible repositories in the index
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🧠 AI-powered enterprise search engine 🔎
- ai
- search-engine
- workplace-search
- enterprise-search
Radically simplified static file serving for Python web apps
Code to pretrain, fine-tune, and evaluate DreamZero and run sim & real-world evals
UAC bypass, Elevate, Persistence methods
YAO = Yielding AI Outcomes. A rigorous engineering, evaluation, governance, and portability system for reusable agent skills.
- agent-skills
- ai-agents
- meta-skill
- skill-engineering
EVA Series: Visual Representation Fantasies from BAAI
- foundation-models
- representation-learning
- vision-transformer
Deep neural network to extract intelligent information from invoice documents.
- invoice
- invoice-management
- invoices
- invoice-insight
Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking, Post Ranking, Relevance, LLM and RL. Please cite our paper "Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives" (TOIS 2026).
- deep-learning
- recommender-system
- search
- advertising
Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends
- evaluation
- evaluation-framework
- evaluation-metrics
- huggingface
A benchmark for evaluating LLMs on Chinese traditional fortune telling — Bazi (八字) and Ziwei Doushu (紫微斗数).
Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
- deep-learning
- flax
- jax
- language-model
HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
- evaluation
- machine-learning
AssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ scenarios, 5 specialist agents (IoT, FMSR, TSFM, Work Order,...), and multi-agent orchestration blueprints (MetaAgent, AgentHive) over MCP.
- llm-agents
- model-context-protocol
- time-series-forecasting
- condition-based-maintenance
[ECCV2024] Video Foundation Models & Data for Multimodal Understanding
- foundation-models
- video-understanding
- vision-transformer
- action-recognition
Build tested agent skills and govern their lifecycle through a user-defined marketplace: evidence, discovery, updates, rollback, quarantine, and 17-platform distribution.
UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.
- machine-learning
- experimentation
- llm-prompting
- llm-test
拼好RAG：手搓并融合了GraphRAG、LightRAG、Neo4j-llm-graph-builder进行知识图谱构建以及搜索；整合DeepSearch技术实现私域RAG的推理；自制针对GraphRAG的评估框架| Integrate GraphRAG, LightRAG, and Neo4j-llm-graph-builder for knowledge graph construction and search. Combine DeepSearch for private RAG reasoning. Create a custom evaluation framework for GraphRAG.
- deepresearch
- deepsearch
- evaluation
- graphrag
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Distributed vector search for AI-native applications
- vectors
- vector-search
- cloud-native
- document-retrieval
The Fable Workflow: how Claude Fable 5 worked, distilled into skills any model can run, with the eval that keeps it honest. Think / act / prove.
Local typed decisions, contrastive data curation, and model evaluation.