Create HG_model+dataset+UI_pipeline_Template.txt

HG_model+dataset+UI_pipeline_Template.txt

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+from transformers import pipeline
+from datasets import load_dataset
+import gradio as gr
+
+# --- Hugging Face Pipeline Setup ---
+# Replace 'model_id' with the identifier of the model you wish to use
+model_id = "declare-lab/flan-alpaca-gpt4-xl"
+text_generator = pipeline(model=model_id)
+
+# --- Dataset Loading (Optional) ---
+# Replace with the dataset of your choice
+dataset_name = "luisotorres/wikipedia-crypto-articles"  # Example dataset
+dataset_split = 'train'  # Choose from 'train', 'test', 'validation', etc.
+dataset = load_dataset(dataset_name, split=dataset_split)
+
+# --- Text Generation Function ---
+def generate_text(prompt, max_tokens=128, system_message=""):
+    # Generating text using the pipeline
+    generated_text = text_generator(prompt, max_length=max_tokens, do_sample=True)[0]["generated_text"]
+
+    # Incorporating the system message
+    full_message = system_message + "\n\nGenerated Text:\n" + generated_text
+    return full_message
+
+# --- Gradio Interface Setup ---
+iface = gr.Interface(
+    fn=generate_text, 
+    inputs=[
+        gr.inputs.Textbox(lines=2, placeholder="Enter Prompt Here..."), 
+        gr.inputs.Slider(minimum=1, maximum=256, default=128, label="Max Tokens"),
+        gr.inputs.Textbox(label="System Message", placeholder="Enter a system message here...")
+    ], 
+    outputs="text"
+)
+
+# --- Launch the Interface ---
+iface.launch()