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LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.
chatgptgpt-4gpt4prompt-engineeringartificial-intelligencedeep-learninglanguage-modelsopenaipythonlangchainlarge-language-modelsllama2
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README
Get SH*T Done with Prompt Engineering and LangChain
Build real-world AI apps with ChatGPT/GPT-4 and LangChain in Python
🍿 Watch on YouTube
- Getting Started with LangChain and Llama 2 in 15 Minutes
- Fine-tuning Llama 2 on Your Own Dataset
- Deploy LLM to Production on Single GPU
- Chat with Multiple PDFs using Llama 2 and LangChain
- AutoGen - Build Powerful AI Agents with ChatGPT/GPT-4
📖 Read the Tutorials
LangChain
- LangChain QuickStart with Llama 2
- Load Custom Data with Loaders
- Add AI with Models
- Make LLMs Useful with Chains
- Build Chatbots with Memory
- Complex Tasks with Agents
Models
- StableVicuna - Open Source RLHF LLM Chatbot
- OpenLLaMa - An Open Reproduction of LLaMA
- XGen-7B: Long Sequence Modeling with (up to) 8K Tokens
- Falcon 180B
Projects
- Fine-tuning Llama 2 on a Custom Dataset
- Chat with Multiple PDFs using Llama 2 and LangChain
- Chatbot with Local LLM (Falcon 7B) and LangChain
- Private GPT4All: Chat with PDF Files Using Free LLM
- CryptoGPT: Crypto Twitter Sentiment Analysis
- Fine-tuning LLM (Falcon 7b) on a Custom Dataset with QLoRA
- Deploy LLM to Production with HuggingFace Inference Endpoints
- Support Chatbot using Custom Knowledge Base with LangChain and Open LLM
- Deploy Your Private Llama 2 Model to Production with RunPod
- AutoGen - Build Powerful AI Agents with ChatGPT/GPT-4
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