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One Path to Bankruptcy for Replit

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,     ...

One Path to Bankruptcy for Replit

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,     ...

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