Add app.py and tokenizer.model

app.py

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+"""from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('tokenizer.model')
+
+categories = ('Rasam', 'Sambar')
+
+def classify_image(img):
+  pred, idx, probs = learn.predict(img)
+  return dict(zip(categories, map(float, probs)))
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['sambar.jpg', 'rasam.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()"""
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "anirudh-sub/debate_model_practice"
+
+def debate_response(text):
+    sequences = pipeline(
+        "How do I give a 1AR in debate in Lincoln Douglas Debate? \n",
+        do_sample=True,
+        top_k=10,
+        num_return_sequences=1,
+        eos_token_id=tokenizer.eos_token_id,
+        max_length=500,
+    )
+
+    response = ""
+    for seq in sequences:
+        reponse += {seq['generated_text']}
+    return resposnse
+
+text = gr.inputs.Text()
+response = gr.outputs.Text()
+intf = gr.Interface(fn=debate_response, inputs=text, outputs=response)

tokenizer.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
+size 499723