Official release of InternLM2 7B and 20B base and chat models. 200K context support
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Updated
Jun 30, 2024 - Python
Official release of InternLM2 7B and 20B base and chat models. 200K context support
An LLM-based Application Tracking System (ATS).
The experiment implements a tiny language model trainer using PyTorch.
The official evaluation suite and dynamic data release for MixEval.
Building AI agents, atomically
An LLM-based application that processes and analyzes your PDFs to deliver context-specific answers.
⚡ Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms⚡
autonomous agent with access to a tool library
Ollama RAG using SQL Database
OpenCompass is an LLM evaluation platform, supporting a wide range of models (Llama3, Mistral, InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
Speech, Language, Audio, Music Processing with Large Language Model
Implementation for MatMul-free LM.
A simple-to-use Python script to generate, maintain, and integrate a visual tree map of your project directory structure for improving LLM performance when dealing with a large codebase
llm-based robot that intervenes only when needed
This is an eldritch project to resurrect the man himself using retrieval augmented generation on his letters
On-device LLM Inference Powered by X-Bit Quantization
LLM4HRS:A LLM-based Spatio-temporal Imputation Model for Highly-sparse Remote Sensing Data
Developed an Azure OpenAI-based RAG email marketing platform with a Streamlit frontend and FIASS vector database for similarity search. The platform processes multiple input formats, including CSV, PDF, text, and PPT, and incorporates product descriptions and sales data to generate creative content and matplotlib graphs based on the input data.
Code for the paper "Match, Compare, or Select? An Investigation of Large Language Models for Entity Matching"
[ACL 2024 Findings] This is the code for our paper "Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models".
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