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import spaces |
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import gradio as gr |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer |
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from threading import Thread |
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""" |
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For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference |
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""" |
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@spaces.GPU |
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def respond( |
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message, |
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history: list[tuple[str, str]], |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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torch.set_default_device("cuda") |
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tokenizer = AutoTokenizer.from_pretrained( |
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"cognitivecomputations/dolphin-2.8-mistral-7b-v02", |
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trust_remote_code=True |
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) |
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model = AutoModelForCausalLM.from_pretrained( |
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"cognitivecomputations/dolphin-2.8-mistral-7b-v02", |
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torch_dtype="auto", |
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load_in_4bit=True, |
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trust_remote_code=True |
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) |
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history_transformer_format = history + [[message, ""]] |
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system_prompt = f"<|im_start|>system\n{system_message}.<|im_end|>" |
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messages = system_prompt + "".join(["".join(["\n<|im_start|>user\n" + item[0], "<|im_end|>\n<|im_start|>assistant\n" + item[1]]) for item in history_transformer_format]) |
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input_ids = tokenizer([messages], return_tensors="pt").to('cuda') |
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streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) |
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generate_kwargs = dict( |
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input_ids, |
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streamer=streamer, |
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max_new_tokens=max_tokens, |
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do_sample=True, |
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top_p=top_p, |
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top_k=50, |
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temperature=temperature, |
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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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partial_message = "" |
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for new_token in streamer: |
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partial_message += new_token |
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if '<|im_end|>' in partial_message: |
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break |
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yield partial_message |
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""" |
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface |
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""" |
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demo = gr.ChatInterface( |
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respond, |
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additional_inputs=[ |
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"), |
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), |
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), |
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gr.Slider( |
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minimum=0.1, |
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maximum=1.0, |
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value=0.95, |
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step=0.05, |
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label="Top-p (nucleus sampling)", |
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), |
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], |
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theme=gr.themes.Soft(primary_hue="green", secondary_hue="indigo", neutral_hue="zinc",font=[gr.themes.GoogleFont("Exo 2"), "ui-sans-serif", "system-ui", "sans-serif"]).set( |
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block_background_fill_dark="*neutral_800" |
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) |
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) |
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if __name__ == "__main__": |
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demo.launch() |
