| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| import os | |
| import gradio as gr | |
| import sentencepiece | |
| from tokenization_yi import YiTokenizer | |
| os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:120' | |
| model_id = "larryvrh/Yi-6B-200K-Llamafied" | |
| tokenizer_path = "./" | |
| eos_token_id = 7 | |
| DESCRIPTION = """ | |
| # 👋🏻Welcome to 🙋🏻♂️Tonic's🧑🏻🚀YI-200K🚀 | |
| You can use this Space to test out the current model [larryvrh/Yi-6B-200K-Llamafied](https://huggingface.co/larryvrh/Yi-6B-200K-Llamafied) a "Llamified" version of [01-ai/Yi-6B-200k](https://huggingface.co/01-ai/Yi-6B-200k) based on [01-ai/Yi-34B](https://huggingface.co/01-ai/Yi-34B) | |
| You can also use 🧑🏻🚀YI-200K🚀 by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic1/YiTonic?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> | |
| Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/nXx5wbX9) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha) | |
| """ | |
| tokenizer = AutoModelForCausalLM.from_pretrained(model_id) | |
| tokenizer = YiTokenizer.from_pretrained(tokenizer_path) | |
| model = AutoModelForCausalLM.from_pretrained(model_id=model_id, device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True) | |
| def format_prompt(user_message, system_message="I am YiTonic, an AI language model created by Tonic-AI. I am a cautious assistant. I carefully follow instructions. I am helpful and harmless and I follow ethical guidelines and promote positive behavior."): | |
| prompt = f"<|im_start|>assistant\n{self.system_message}<|im_end|>\n<|im_start|>\nuser\n{user_message}<|im_end|>\nassistant\n" | |
| return prompt | |
| def predict(message, system_message, max_new_tokens=4056, temperature=3.5, top_p=0.9, top_k=800, do_sample=False): | |
| formatted_prompt = format_prompt(message, system_message) | |
| input_ids = tokenizer.encode(formatted_prompt, return_tensors='pt') | |
| input_ids = input_ids.to(model.device) | |
| response_ids = model.generate( | |
| input_ids, | |
| max_length=max_new_tokens + input_ids.shape[1], | |
| temperature=temperature, | |
| top_p=top_p, | |
| top_k=top_k, | |
| no_repeat_ngram_size=5, | |
| pad_token_id=tokenizer.eos_token_id, | |
| do_sample=do_sample | |
| ) | |
| response = tokenizer.decode(response_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True) | |
| return [("bot", response)] | |
| with gr.Blocks(theme='ParityError/Anime') as demo: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Group(): | |
| textbox = gr.Textbox(placeholder='Your Message Here', label='Your Message', lines=2) | |
| system_prompt = gr.Textbox(placeholder='Provide a System Prompt In The First Person', label='System Prompt', lines=2, value="You are YiTonic, an AI language model created by Tonic-AI. You are a cautious assistant. You carefully follow instructions. You are helpful and harmless and you follow ethical guidelines and promote positive behavior.") | |
| with gr.Group(): | |
| submit_button = gr.Button('Submit', variant='primary') | |
| with gr.Accordion(label='Advanced options', open=False): | |
| max_new_tokens = gr.Slider(label='Max New Tokens', minimum=1, maximum=55000, step=1, value=4056) | |
| temperature = gr.Slider(label='Temperature', minimum=0.1, maximum=4.0, step=0.1, value=1.2) | |
| top_p = gr.Slider(label='Top-P (nucleus sampling)', minimum=0.05, maximum=1.0, step=0.05, value=0.9) | |
| top_k = gr.Slider(label='Top-K', minimum=1, maximum=1000, step=1, value=900) | |
| do_sample_checkbox = gr.Checkbox(label='Disable for faster inference', value=False) | |
| submit_button.click( | |
| fn=predict, | |
| inputs=[textbox, system_prompt, max_new_tokens, temperature, top_p, top_k, do_sample_checkbox], | |
| outputs=chatbot | |
| ) | |
| with gr.Group(): | |
| chatbot = gr.Chatbot(label='TonicYi-6B-200K-🦙') | |
| demo.launch() |