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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
# Load the model from Hugging Face Hub
MODEL_NAME = "tacab/somali-agriculture"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
# Create text generation pipeline
generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
# Function to use in the Gradio interface
def generate_text(prompt):
output = generator(
prompt,
do_sample=True,
max_length=200,
pad_token_id=tokenizer.eos_token_id
)
return output[0]["generated_text"]
# Build Gradio interface
gr.Interface(
fn=generate_text,
inputs=gr.Textbox(lines=3, label="Geli qoraalka/Prompt-ka"),
outputs=gr.Textbox(label="Natiijada/Generated Text"),
title="Tacab – Somali Agriculture Generator",
description="App-kan wuxuu adeegsadaa model-ka 'tacab/somali-agriculture' si uu u abuuro qoraal cusub oo la xiriira beeraha Soomaaliyeed."
).launch()
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