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import gradio as gr
gr.load("models/ai-forever/ruGPT-3.5-13B").launch()
model = AutoModel.from_pretrained("models/ai-forever/ruGPT-3.5-13B")
tokenizer = AutoTokenizer.from_pretrained("models/ai-forever/ruGPT-3.5-13B")
print('launch')
def greet(request):
print('greet')
encoded_input = tokenizer(request, return_tensors='pt', \
add_special_tokens=False).to('cuda:0')
print('encoded_input')
output = model.generate(
**encoded_input,
num_beams=2,
do_sample=True,
max_new_tokens=100
)
print('output')
return tokenizer.decode(output[0], skip_special_tokens=True)
iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch() |