Initail Commit

Dockerfile

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+# Use an official Python runtime as the base image
+FROM python:3.8-slim
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the local code and requirements.txt to the container
+COPY . /app/
+
+# Install necessary Python packages from requirements.txt
+RUN pip install --upgrade pip && \
+    pip install -r requirements.txt
+
+# Make port 7860 available to the world outside this container (default port for Gradio)
+EXPOSE 7860
+
+# Define an environment variable (Optional)
+# This can be used to set Gradio server name, port, etc.
+# ENV GRADIO_SERVER_NAME 0.0.0.0
+# ENV GRADIO_SERVER_PORT 7860
+
+# Run your script when the container launches
+CMD ["python", "app.py"]

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+
+model = "tiiuae/falcon-180b-chat"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+    device_map="auto",
+)
+
+def generate_headlines(topic):
+    sequences = pipeline(
+       f"Create at most 5 headlines that highlight {topic}. The headlines should be concise, attention-grabbing, and suitable for use in a news video.",
+        max_length=200,
+        do_sample=True,
+        top_k=10,
+        num_return_sequences=5,
+        eos_token_id=tokenizer.eos_token_id,
+    )
+    headlines = [seq['generated_text'] for seq in sequences]
+    return "\n".join(headlines)
+
+iface = gr.Interface(
+    fn=generate_headlines,
+    inputs=gr.inputs.Textbox(placeholder="Enter the topic"),
+    outputs="text",
+    examples=[["Climate Change"], ["AI Innovations"], ["Space Exploration"]]
+)
+
+iface.launch()

requirements.txt

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+gradio
+transformers
+torch