Create app.py
Browse files
app.py
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import gradio as gr
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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from threading import Thread
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model = AutoModelForCausalLM.from_pretrained("icechat")
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tokenizer = AutoTokenizer.from_pretrained("icechat")
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def streaming_respond(question, history):
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input_ids = tokenizer.encode("### Question: " + question, return_tensors="pt")
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streamer = TextIteratorStreamer(
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tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True
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)
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generate_kwargs = dict(
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{"input_ids": input_ids},
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streamer=streamer,
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max_new_tokens=10,
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num_beams=1,
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)
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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t.start()
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outputs = []
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for text in streamer:
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outputs.append(text)
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yield "".join(outputs)
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gr.ChatInterface(streaming_respond).launch()
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