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Update app.py
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app.py
CHANGED
@@ -2,9 +2,14 @@ import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221")
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model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221")
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st.write(model.__class__.__name__)
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@@ -22,23 +27,27 @@ model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pic
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st.write(model.__class__.__name__)
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st.code(type(model))
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extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
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model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
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st.write(model.__class__.__name__)
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st.code(type(model))
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extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225")
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model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225")
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st.write(model.__class__.__name__)
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st.code(type(model))
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from datasets import load_dataset
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dataset = load_dataset("rwcuffney/pick_a_card_test")
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'''
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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import pandas as pd
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import matplotlib.pyplot as plt
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from datasets import load_dataset
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dataset = load_dataset("rwcuffney/pick_a_card_test")
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#tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
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#tokenized_data = tokenizer(dataset["sentence"], return_tensors="np", padding=True)
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from transformers import AutoFeatureExtractor, AutoModelForImageClassification
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'''
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extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221")
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model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221")
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st.write(model.__class__.__name__)
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st.write(model.__class__.__name__)
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st.code(type(model))
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'''
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extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
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model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
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st.write(model.__class__.__name__)
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st.code(type(model))
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from transformers import AutoImageProcessor
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import torch
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image_processor = AutoImageProcessor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224"))
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inputs = image_processor(image, return_tensors="pt")
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'''
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extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225")
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model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225")
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st.write(model.__class__.__name__)
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st.code(type(model))
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'''
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'''
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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