User trying to import a module that's not installed. Instead of bumping him and telling her to use a different workspace on which the module *is* installed, use compute resources to try and install.. nuts.. Starting with : from transformers import TFAutoModelForSeq2SeqLM, AutoTokenizer import gradio as gr model = TFAutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small") tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small") def gen_text(input_string, max_length): inputs = tokenizer(input_string, return_tensors="pt") outputs = model.generate(**inputs, max_length=max_length) final_text = tokenizer.batch_decode(outputs[0], skip_special_tokens=True) return (final_text) demo = gr.Interface( fn=gen_text, ...
The short summary : "How to shoot yourself in the foot by running Jupyter on two different operating systems simultaneously (on the same computer)" BLUF : Are you sure the notebook in Chrome isn't using a different Jupyter session than you think? Check! What? How? Why? I got a new work computer, on which I didn't have Administrator rights, to be able to install WSL. (Didn't know *how* to get admin rights 😊). So, being a guy who needs an Excel dashboard and a notebook open all the time, I installed Git bash just to get a flavor of unix (why? Because I can then run my own search engine to search notes for solutions to problems encountered in the past) This gives me Jupyter labs (though I'm happy with plain v Jupe). And I'm kind of hooked. It looks cute. Eventually, I get WSL on there because I need something industrial, not wimpy Git bash that looks like a cygwin under the hood :) And, when the time comes to try hacking, like an openCV course, I nee...