LabLab.ai Falcon LLM Hackathon
Submitted Project: https://lablab.ai/event/falcon-llms-24-hours-hackathon/fritzlabs/everdiver
Falcon is an open-source LLM from the Technology Innovation Institute. Falcon offers the chance to deploy an open-source large language model locally. This allows to preserve privacy working with your personal evernote data. As such this project is part of the lablabai falcon hackathon.
- create dummy evernote data
- extract data from evernote exported enex file
- deploy/serve falcon llm locally or in private free cloud environment (kaggle, colab, saturncloud) or connect to hosting service (clarifai)
- connect enex data to deployed llm using tools such as llamaindex or langchain
streamlit run streamlit-app/app.py
When will be lunch break according to the schedule on Friday?
Lunch break will be at 12:30 pm on Friday according to the schedule.
Which books on my reading list are authored by Jack London?
"The Call of the Wild", "White Fang", and "The Sea-Wolf" are all authored by Jack London.
Which sections does the essay have?
The essay has three sections: 1. Introduction 2. Body 3. Conclusion
What is the project about that is described in the project plan?
The project plan describes the process of building a chain of ice cream shops in the local region.
- https://github.com/putuwaw/docutalk Apache 2.0 open source license
- https://www.kaggle.com/code/hinepo/q-a-chatbot-with-llms-harry-potter Apache 2.0 open source license
- https://github.com/nomic-ai/gpt4all
- https://github.com/bentoml/OpenLLM
- https://github.com/vllm-project/vllm
- https://github.com/skypilot-org/skypilot
- https://github.com/basetenlabs/truss-examples
- https://github.com/TimDettmers/bitsandbytes Quantization GPU
Evernote does not offer the possibility to analyze your notes collection. Python can be used to access the local evernote database or exported note files and analyze the information it contains.
- show areas of expertise
- display the depths of knowledge in each corresponding field (beginner vs expert)
- show time course of creating/updating notes in each knowledge field
- visualize connection between notes
- identify missing knowledge comparing to outside databases