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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load model
model_name = "EleutherAI/pythia-1.4B-deduped"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Device
device = torch.device("cpu")
model.to(device)
def generate(prompt):
inputs = tokenizer(prompt, return_tensors="pt").to(device)
outputs = model.generate(
**inputs,
max_new_tokens=200,
do_sample=True,
temperature=0.7
)
text = tokenizer.decode(outputs[0], skip_special_tokens=True)
return text
# Gradio interface làm API
iface = gr.Interface(
fn=generate,
inputs=gr.Textbox(lines=5, placeholder="Nhập prompt…"),
outputs=gr.Textbox(),
title="OASST-J-3B API"
)
iface.launch(server_name="0.0.0.0", server_port=7860)
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