AI/ML

Falcon 40B is currently the best-performing open source Large Language Model (LLM) in the world. In this video, we'll explore how to use the model with Hugging Face Transformers and LangChain to create a chatbot and conversational agent. 📌 Code Notebook: https://github.com/pinecone-io/examples/blob/master/generation/llm-field-guide/falcon-40b/falcon-40b-chatbot.ipynb 👋🏼 NLP + LLM Consulting: https://aurelio.ai 🎙️ Support me on Patreon: https://patreon.com/JamesBriggs 👾 Discord: https://discord.gg/c5QtDB9RAP Twitter: https://twitter.com/jamescalam LinkedIn: https://www.linkedin.com/in/jamescalam/ Instagram: https://www.instagram.com/jamescalam/ 00:00 Falcon 40B Instruct LLM 01:48 Falcon 40B in Python 07:04 Falcon 40B Chatbot in LangChain 09:31 Handling Output with Output Parsers 13:31 Falcon 40B as Chatbot and Code Generation 15:45 Refactoring Code with Falcon 40B and GPT 3.5 19:14 Falcon 40B as an Agent 21:34 Final Thoughts #artificialintelligence #nlp #langchain #opensource

In this video I show I was able to install an open source Large Language Model (LLM) called h2oGPT on my local computer for 100% private, 100% local chat wit...

In two recent conversations with very thoughtful journalists, I was asked about the apparent ‘schism’ between those making a lot of noise…

Firstly, which AI tools are worth running?

With the emergence of LLM “AI”, everyone will have to learn what many disabled people have always understood

Fall is going to be very different this year. Educators need to be ready.

Trick Gandalf into revealing information and experience the limitations of large language models firsthand.

Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver. Agent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components:

Run inference on MPT-30B using CPU. Contribute to abacaj/mpt-30B-inference development by creating an account on GitHub.