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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load DeepSeek model
model_id = "deepseek-ai/deepseek-llm-7b-chat"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
def generate_response(prompt, temperature):
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(
**inputs,
do_sample=True,
temperature=temperature,
top_p=0.9
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# return "Hello " + name + "!!"
demo = gr.Interface(fn=generate_response,
inputs=[
gr.Textbox(label="Prompt", lines=6, placeholder="Ask something..."),
gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
],
outputs="text"
)
demo.launch() |