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Runtime error
| import streamlit as st | |
| from transformers import pipeline | |
| from PIL import Image | |
| from instruct_pipeline import InstructionTextGenerationPipeline | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| tokenizer = AutoTokenizer.from_pretrained("databricks/dolly-v2-3b", padding_side="left") | |
| model = AutoModelForCausalLM.from_pretrained("databricks/dolly-v2-3b", device_map="auto") | |
| generate_text = InstructionTextGenerationPipeline(model=model, tokenizer=tokenizer) | |
| text=generate_text("Explain to me the difference between nuclear fission and fusion.") | |
| st.title(text) | |
| file_name = st.file_uploader("Upload a hot dog candidate image") | |
| if file_name is not None: | |
| col1, col2 = st.columns(2) | |
| image = Image.open(file_name) | |
| col1.image(image, use_column_width=True) | |
| predictions = pipeline(image) | |
| col2.header(text) | |
| for p in predictions: | |
| col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%") |