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Runtime error
| import streamlit as st | |
| from transformers import pipeline | |
| # The one with 'sentiment-analysis' | |
| pipe = pipeline('sentiment-analysis') | |
| test = st.text_area('enter the text:') | |
| if test: | |
| out = pipe(test) | |
| st.json(out) | |
| # The one with "text-classification" | |
| pipe_one = pipeline('question-answering') | |
| test_one = st.text_area('enter more text:') | |
| if test: | |
| out_one = pipe_one(test_one) | |
| st.json(out_one) | |
| # text generation from youtube vid | |
| # st.write("And now for something completely different...") | |
| # | |
| # default_value = "See how a modern neural network auto-completes your text using HuggingFace" | |
| # st.write("\n\nThe King of Text Generation, GPT-2 comes in four available sizes, only three of which have been made publicly available.") | |
| # | |
| # sent = st.text_area("Text", defalut_value, height=275) | |
| # max_length = st.sidebar.slider("Max Length", min_value = 10, max_value=30) | |
| # temperature = st.sidebar.slider("Temperature", value = 1.0, min_value=0.0, max_value=1.0, step=0.05) | |
| # top_k = st.sidebar.slider("Top-k", min_value=0, max_value=5, value=0) | |
| # top_p = st.sidebar.slider("top-p", min_value=0.0, max_value=1.0, step=0.05, value=0.9) | |
| # num_return_sequences = st.sidebar.number_input('Number of Return Sequences', min_value=1, max_value=5, value=1, step=1) | |
| # | |
| # encoded_prompt = tokenizer.encode(sent, add_special_tokens=False, return_tensors="pt") | |
| # if encoded_prompt.size()[-1] == 0: | |
| # input_ids = None | |
| # else: | |
| # input_ids = encoded_prompt | |
| # | |
| # output_sequences = infer(input_ids, max_length, temperature, top_k, top_p, num_return_sequences) | |
| # | |
| # for generated_sequence_idx, generated_sequence in enumerate(output_sequences): | |
| # print(f"=== GENERATED SEQUENCE {generated_sequence_idx + 1} ===") | |