completly undocumented -- but maybe you'll find something burried here ?
Note: We are using Lamda Stack on production/dev server
Setup Python Venv
python3 -m venv lambda-stack-with-tensorflow-pytorch --system-site-packages
Launch Server
source lambda-stack-with-tensorflow-pytorch/bin/activate
pnpm run dev
python server.py
sudo tailscale funnel --https 443 http://127.0.0.1:3000
sudo tailscale funnel --https 8443 http://127.0.0.1:8000
Somthing like this but for chatgpt conversation flow:
Entity Typing
Interpretable Entity Representations through Large-Scale Typing
Legal Bert
https://huggingface.co/nlpaueb/legal-bert-base-uncased
unfortunately this model is uncased, I would think cased would be more useful in legal tasks where defined terms are usually cased.
Entity Typing:
- requires the model to predict the fine-grained types of a set of free-form phrases given their context
Relation Extraction:
- the model identifies the specific semantic relationship between two entities within a provided sentence.
Text 2 Triplet
Knowledge Graph Completion
Hyper Relational Knowledge Graphs