Shivam Thakkar

I am facing the same issue. As far as I understand the issue is with the keras compatibility of the tensorflow backend. I am using the following versions - keras==2.4.3...

Thanks @bedapudi6788, it worked with - keras==2.3.1 tensorflow==2.2.0 Also for tensorflow 1, it works fine with the versions - keras==2.2.4 tensorflow==1.14.0 ## Few Suggestions - - I think the original...

If you could elaborate on what exact problem are you solving, maybe one can help you with the specific dataset you are looking for.

Here no training is done. Actually, they have used a pre-trained [FaceNet](https://arxiv.org/pdf/1503.03832.pdf) model which is designed to learn how to distinguish between two faces in Euclidean Space. The main idea...

If you refer to the [node2vec paper](https://cs.stanford.edu/people/jure/pubs/node2vec-kdd16.pdf) on page 5 you can find that one can use multiple methods to calculate edge embeddings from node embeddings using simple mathematical formulas....

For keycloak the following worked for me - ``` @app.route('/logout') @oidc.require_login def logout(): refresh_token = oidc.get_refresh_token() oidc.logout() keycloak_openid.logout(refresh_token) response = redirect(url_for('login')) return response ``` I used [python-keycloak](https://github.com/marcospereirampj/python-keycloak) library to logout...

@varun-g91 had the same issue earlier, probably it has to do with ngrok tunneling with ollama version > 1.2.8 can you try replacing: `run_process(['ngrok', 'http', '--log', 'stderr', '11434'])` with: `run_process(['ngrok',...