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| import streamlit as st | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| from datasets import load_dataset | |
| dataset = load_dataset("rwcuffney/pick_a_card_test") | |
| #tokenizer = AutoTokenizer.from_pretrained("bert-base-cased") | |
| #tokenized_data = tokenizer(dataset["sentence"], return_tensors="np", padding=True) | |
| from transformers import AutoFeatureExtractor, AutoModelForImageClassification | |
| ''' | |
| extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221") | |
| model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221") | |
| st.write(model.__class__.__name__) | |
| st.code(type(model)) | |
| extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099222") | |
| model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099222") | |
| st.write(model.__class__.__name__) | |
| st.code(type(model)) | |
| extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099223") | |
| model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099223") | |
| st.write(model.__class__.__name__) | |
| st.code(type(model)) | |
| ''' | |
| extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224") | |
| model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224") | |
| st.write(model.__class__.__name__) | |
| st.code(type(model)) | |
| from transformers import AutoImageProcessor | |
| import torch | |
| image = dataset["test"][0] | |
| st.image(image) | |
| image_processor = AutoImageProcessor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224") | |
| inputs = image_processor(image, return_tensors="pt") | |
| ''' | |
| extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225") | |
| model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225") | |
| st.write(model.__class__.__name__) | |
| st.code(type(model)) | |
| ''' | |
| ''' | |
| x = st.slider('Select a value') | |
| st.write(x, 'squared is', x * x) | |
| import pandas as pd | |
| #df = pd.read_csv('https://rwcuffney/autotrain-data-pick_a_card/cards.csv').sort_values('class index') | |
| #st.dataframe(df.head(3)) | |
| # from datasets import load_dataset | |
| dataset = load_dataset("https://rwcuffney/autotrain-data-pick_a_card") | |
| # st.write(type(dataset)) | |
| # st.write('Hello World') | |
| from datasets import load_dataset | |
| #dataset = load_dataset("rwcuffney/autotrain-data-pick_a_card") | |
| #st.write(dataset) | |
| import pandas as pd | |
| import requests | |
| import io | |
| # Downloading the csv file from your GitHub account | |
| url = "https://huggingface.co/datasets/rwcuffney/autotrain-data-pick_a_card/raw/main/cards.csv" # Make sure the url is the raw version of the file on GitHub | |
| download = requests.get(url).content | |
| # Reading the downloaded content and turning it into a pandas dataframe | |
| df = pd.read_csv(io.StringIO(download.decode('utf-8'))) | |
| #df = pd.read_csv('playing_cards/cards.csv').sort_values('class index') | |
| df_test = df[df['data set']=='test'] | |
| df_train = df[df['data set']=='train'] | |
| df_validate = df[df['data set']=='validate'] | |
| from datasets import load_dataset #this isn't working | |
| dataset = load_dataset("rwcuffney/pick_a_card_test") #rwcuffney/pick_a_card_test | |
| st.write(df.head(20)) | |
| ### | |
| ''' |