Initial commit for Dad Jokes App

.gradio/certificate.pem

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.gradio/flagged/dataset1.csv

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+name,output,timestamp
+Stephen Oke,Hello Stephen Oke!!,2025-02-19 11:30:13.461029

DadJokes/.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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DadJokes/README.md

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+---
+title: DadJokes
+emoji: 📚
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 5.16.1
+app_file: app.py
+pinned: false
+short_description: puns and dad jokes
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+import datasets
+import pandas as pd
+from datasets import Dataset
+
+# Load GPT-2 model and tokenizer
+model_name = "gpt2"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# # Text generation pipeline
+# generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+
+
+
+def load_jokes_dataset(word):
+   # Load the dataset
+    df = pd.read_csv("short-jokes.csv")
+    
+    # Filter jokes that contain the input word (case-insensitive)
+    filtered_jokes = df[df['joke'].str.contains(word, case=False, na=False)]
+    
+    # Return a random joke if there are matches, otherwise return a message
+    if not filtered_jokes.empty:
+        return filtered_jokes.sample(n=1).iloc[0]['joke']
+    else:
+        return "No jokes found with that word! Try another word 😊"
+
+
+
+with gr.Blocks(css=".button-custom {background-color: #FF5733; color: orange; font-size: 18px; border-radius: 12px; padding: 12px 20px; border: none; cursor: pointer;}") as demo:
+    gr.Markdown("**Dad Joke Generator**")
+    gr.Markdown("just type a word and ill make a dad joke out of it")
+    word_input = gr.Textbox(label="Enter a word")
+    output = gr.Textbox(" ")
+    button = gr.Button("Submit")
+    button.click(fn=load_jokes_dataset,inputs=word_input, outputs=output)
+demo.launch(share=True)

requirements.txt

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+gradio
+transformers
+datasets
+torch
+pandas