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Running
on
T4
Running
on
T4
| from transformers import AutoModel, AutoTokenizer | |
| import gradio as gr | |
| tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) | |
| model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda() | |
| model = model.eval() | |
| def predict(input, history=None): | |
| if history is None: | |
| history = [] | |
| response, history = model.chat(tokenizer, input, history) | |
| return history, history | |
| with gr.Blocks() as demo: | |
| gr.Markdown('''## ChatGLM-6B - unofficial demo | |
| Unnoficial demo of the [ChatGLM-6B](https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md) model, trained on 1T tokens of English and Chinese | |
| ''') | |
| state = gr.State([]) | |
| chatbot = gr.Chatbot([], elem_id="chatbot").style(height=400) | |
| with gr.Row(): | |
| with gr.Column(scale=4): | |
| txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False) | |
| with gr.Column(scale=1): | |
| button = gr.Button("Generate") | |
| txt.submit(predict, [txt, state], [chatbot, state]) | |
| button.click(predict, [txt, state], [chatbot, state]) | |
| demo.queue().launch() |