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import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
# Load the model and tokenizer | |
model_name = "hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode" | |
model = AutoModelForCausalLM.from_pretrained(model_name) | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
def generate_text(prompt): | |
inputs = tokenizer(prompt, return_tensors="pt") | |
outputs = model.generate(**inputs) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
# Create a Gradio interface | |
iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Meta-Llama-3-8B Text Generation") | |
iface.launch() | |