LLM on AWS SageMaker Examples

A standard SageMaker notebook instance should be sufficient to run below demos. e.g. "ml.t3.medium"

chatglm2-langchain-vetordb_deploy.ipynb is an example for deploying THUDM/chatglm2-6b with vectorDB Chroma and LangChain on AWS SageMaker Platform, targeting at building private query-answer system powered by vectorDB and LLM.
baichuan13b-langchain-vetordb_deploy.ipynb is an example for deploying baichuan-inc/Baichuan-13B-Chat with vectorDB Chroma and LangChain(ducument processing only) on AWS SageMaker Platform, targeting at building private query-answer system powered by vectorDB and LLM.
chatglm3-streaming-deploy.ipynb is a streaming outputs example deployed on SageMaker.
bedrock-langchain-vectordb.ipynb is an example for combining bedrock-claude with vectorDB for llm+RAG usecase.
bedrock-knowledgebase-streamlit.ipynb is an example for combining bedrock-claude, KnowledgeBase and Streamlit for llm+RAG usecase.

Stay tuned ...

Name		Name	Last commit message	Last commit date
Latest commit History 44 Commits
content		content
README.md		README.md
baichuan13b-langchain-vectordb_deploy.ipynb		baichuan13b-langchain-vectordb_deploy.ipynb
bedrock-knowledgebase-streamlit.ipynb		bedrock-knowledgebase-streamlit.ipynb
bedrock-langchain-vectordb.ipynb		bedrock-langchain-vectordb.ipynb
chatglm2-langchain-vectordb_deploy.ipynb		chatglm2-langchain-vectordb_deploy.ipynb
chatglm3-streaming-deploy.ipynb		chatglm3-streaming-deploy.ipynb
requirements.txt		requirements.txt
streamlit_chatbot.py		streamlit_chatbot.py

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