| import os | |
| import gradio as gr | |
| from llama_cpp import Llama | |
| from huggingface_hub import hf_hub_download | |
| model = Llama( | |
| model_path=hf_hub_download( | |
| repo_id=os.environ.get("REPO_ID", "SimpleBerry/LLaMA-O1-Supervised-1129-Q2_K-GGUF"), | |
| filename=os.environ.get("MODEL_FILE", "LLaMA-O1-Supervised-1129-q2_k.gguf"), | |
| ) | |
| ) | |
| DESCRIPTION = ''' | |
| # SimpleBerry/LLaMA-O1-Supervised-1129 | Duplicate the space and set it to private for faster & personal inference for free. | |
| SimpleBerry/LLaMA-O1-Supervised-1129: an experimental research model developed by the SimpleBerry. | |
| Focused on advancing AI reasoning capabilities. | |
| ## This Space was designed by Lyte/LLaMA-O1-Supervised-1129-GGUF, Many Thanks! | |
| **To start a new chat**, click "clear" and start a new dialog. | |
| ''' | |
| LICENSE = """ | |
| --- MIT License --- | |
| """ | |
| template = "<start_of_father_id>-1<end_of_father_id><start_of_local_id>0<end_of_local_id><start_of_thought><problem>{content}<end_of_thought><start_of_rating><positive_rating><end_of_rating>\n<start_of_father_id>0<end_of_father_id><start_of_local_id>1<end_of_local_id><start_of_thought><expansion>" | |
| def llama_o1_template(data): | |
| #query = data['query'] | |
| text = template.format(content=data) | |
| return text | |
| def generate_text(message, history, max_tokens=512, temperature=0.9, top_p=0.95): | |
| temp = "" | |
| input_texts = [llama_o1_template(message)] | |
| input_texts = [input_text.replace('<|end_of_text|>','') for input_text in input_texts] | |
| #print(f"input_texts[0]: {input_texts[0]}") | |
| inputs = model.tokenize(input_texts[0].encode('utf-8')) | |
| for token in model.generate(inputs, top_p=top_p, temp=temperature): | |
| #print(f"token: {token}") | |
| text = model.detokenize([token]) | |
| #print(f"text detok: {text}") | |
| temp += text.decode('utf-8') | |
| yield temp | |
| with gr.Blocks() as demo: | |
| gr.Markdown(DESCRIPTION) | |
| chatbot = gr.ChatInterface( | |
| generate_text, | |
| title="SimpleBerry/LLaMA-O1-Supervised-1129 | GGUF Demo", | |
| description="Edit Settings below if needed.", | |
| examples=[ | |
| ["How many r's are in the word strawberry?"], | |
| ['If Diana needs to bike 10 miles to reach home and she can bike at a speed of 3 mph for two hours before getting tired, and then at a speed of 1 mph until she reaches home, how long will it take her to get home?'], | |
| ['Find the least odd prime factor of $2019^8+1$.'], | |
| ], | |
| cache_examples=False, | |
| fill_height=True | |
| ) | |
| with gr.Accordion("Adjust Parameters", open=False): | |
| gr.Slider(minimum=128, maximum=8192, value=512, step=1, label="Max Tokens") | |
| gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature") | |
| gr.Slider(minimum=0.05, maximum=1.0, value=0.95, step=0.01, label="Top-p (nucleus sampling)") | |
| gr.Markdown(LICENSE) | |
| if __name__ == "__main__": | |
| demo.launch() | |
| # # import spaces | |
| # import os | |
| # import gradio as gr | |
| # from transformers import AutoTokenizer, AutoModelForCausalLM | |
| # from huggingface_hub import hf_hub_download, snapshot_download | |
| # import accelerate | |
| # accelerator = accelerate.Accelerator() | |
| # # Load the model and tokenizer from Hugging Face | |
| # model_path = snapshot_download( | |
| # repo_id=os.environ.get("REPO_ID", "SimpleBerry/LLaMA-O1-Supervised-1129") | |
| # ) | |
| # tokenizer = AutoTokenizer.from_pretrained(model_path) | |
| # model = AutoModelForCausalLM.from_pretrained(model_path,device_map='auto') | |
| # DESCRIPTION = ''' | |
| # # SimpleBerry/LLaMA-O1-Supervised-1129 | Duplicate the space and set it to private for faster & personal inference for free. | |
| # SimpleBerry/LLaMA-O1-Supervised-1129: an experimental research model developed by the SimpleBerry. | |
| # Focused on advancing AI reasoning capabilities. | |
| # ## This Space was designed by Lyte/LLaMA-O1-Supervised-1129-GGUF, Many Thanks! | |
| # **To start a new chat**, click "clear" and start a new dialogue. | |
| # ''' | |
| # LICENSE = """ | |
| # --- MIT License --- | |
| # """ | |
| # template = "<start_of_father_id>-1<end_of_father_id><start_of_local_id>0<end_of_local_id><start_of_thought><problem>{content}<end_of_thought><start_of_rating><positive_rating><end_of_rating>\n<start_of_father_id>0<end_of_father_id><start_of_local_id>1<end_of_local_id><start_of_thought><expansion>" | |
| # def llama_o1_template(data): | |
| # #query = data['query'] | |
| # text = template.format(content=data) | |
| # return text | |
| # def format_response(response): | |
| # response = response.replace('<start_of_father_id>','') | |
| # response = response.replace('<end_of_father_id><start_of_local_id>','👉') | |
| # response = response.replace('<end_of_local_id><start_of_thought>',', ') | |
| # response = response.replace('<end_of_thought><start_of_rating>','') | |
| # response = response.replace('<end_of_rating>','') | |
| # response = response.replace('<positive_rating>','👍') | |
| # response = response.replace('<negative_rating>','👎') | |
| # # @spaces.GPU | |
| # def generate_text(message, history, max_tokens=512, temperature=0.9, top_p=0.95): | |
| # input_text = llama_o1_template(message) | |
| # inputs = tokenizer(input_text, return_tensors="pt").to(accelerator.device) | |
| # # Generate the text with the model | |
| # output = model.generate( | |
| # **inputs, | |
| # max_length=max_tokens, | |
| # temperature=temperature, | |
| # top_p=top_p, | |
| # do_sample=True, | |
| # ) | |
| # response = tokenizer.decode(output[0], skip_special_tokens=False) | |
| # yield response | |
| # with gr.Blocks() as demo: | |
| # gr.Markdown(DESCRIPTION) | |
| # chatbot = gr.ChatInterface( | |
| # generate_text, | |
| # title="SimpleBerry/LLaMA-O1-Supervised-1129 | GGUF Demo", | |
| # description="Edit Settings below if needed.", | |
| # examples=[ | |
| # ["How many r's are in the word strawberry?"], | |
| # ['If Diana needs to bike 10 miles to reach home and she can bike at a speed of 3 mph for two hours before getting tired, and then at a speed of 1 mph until she reaches home, how long will it take her to get home?'], | |
| # ['Find the least odd prime factor of $2019^8+1$.'], | |
| # ], | |
| # cache_examples=True, | |
| # fill_height=True, | |
| # ) | |
| # with gr.Accordion("Adjust Parameters", open=False): | |
| # gr.Slider(minimum=1024, maximum=8192, value=2048, step=1, label="Max Tokens") | |
| # gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature") | |
| # gr.Slider(minimum=0.05, maximum=1.0, value=0.95, step=0.01, label="Top-p (nucleus sampling)") | |
| # gr.Markdown(LICENSE) | |
| # if __name__ == "__main__": | |
| # demo.launch() |