Improved file parsing for LLM’s
- document-structure
- table-detection
- document-parser
- layout-parsing
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Improved file parsing for LLM’s
[EMNLP 2023 Demo] Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
AI Powered Knowledge Graph Generator
QuantMind is an open source agent-native knowledge extraction and retrieval framework for quantitative finance.
Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo
RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers.
Advanced CLI tool that scans your hardware and tells you exactly which LLM or sLLM models you can run locally, with full Ollama integration.
Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.
An open-source visual programming environment for battle-testing prompts to LLMs.
A framework for prompt tuning using Intent-based Prompt Calibration
Open-source desktop AI agent for tools, files, knowledge, workflows, and real deliverables.
NeMo Retriever Library is a scalable, performance-oriented document content and metadata extraction microservice. NeMo Retriever Library uses specialized NVIDIA NIM microservices to find, contextualize, and extract text, tables, charts and images that you can use in downstream generative applications.
README file generator, powered by AI.
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
Find the ghost tokens. Fix them. Survive compaction. Avoid context quality decay.
mean Average Precision - This code evaluates the performance of your neural net for object recognition.
Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparent evaluation of foundation models, including large language models (LLMs) and multimodal models.
C++ implementation of ChatGLM-6B & ChatGLM2-6B & ChatGLM3 & GLM4(V)
A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
⚡LLM Zoo is a project that provides data, models, and evaluation benchmark for large language models.⚡
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InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
Reference implementation for DPO (Direct Preference Optimization)