import gradio as gr import os os.system('CMAKE_ARGS="-DLLAMA_OPENBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python') import wget from llama_cpp import Llama import random import os import multiprocessing def get_num_cores(): """Get the number of CPU cores.""" return os.cpu_count() def get_num_threads(): """Get the number of threads available to the current process.""" return multiprocessing.cpu_count() if __name__ == "__main__": num_cores = get_num_cores() num_threads = get_num_threads() print(f"Number of CPU cores: {num_cores}") print(f"Number of threads available to the current process: {num_threads}") url = 'https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/resolve/main/llama-2-7b-chat.ggmlv3.q2_K.bin' filename = wget.download(url) llm2 = Llama(model_path=filename, seed=random.randint(1, 2**31), lora_path="ggml-adapter-model (1).bin") filename = wget.download(url) theme = gr.themes.Soft( primary_hue=gr.themes.Color("#ededed", "#fee2e2", "#fecaca", "#fca5a5", "#f87171", "#ef4444", "#dc2626", "#b91c1c", "#991b1b", "#7f1d1d", "#6c1e1e"), neutral_hue="red", ) title = """

Chat with awesome LLAMA 2 CHAT model!


""" with gr.Blocks(theme=theme) as demo: gr.HTML(title) gr.HTML("This model is awesome for its size! It is only 20th the size of Chatgpt but is still decent for chatting. However like all models, LLAMA-2-CHAT can hallucinate and provide incorrect information.") #chatbot = gr.Chatbot() #msg = gr.Textbox() #clear = gr.ClearButton([msg, chatbot]) #instruction = gr.Textbox(label="Instruction", placeholder=) def bot(user_message): #token1 = llm.tokenize(b"### Instruction: ") #token2 = llm.tokenize(instruction.encode()) #token3 = llm2.tokenize(b"USER: ") #tokens3 = llm2.tokenize(user_message.encode()) #token4 = llm2.tokenize(b"\n\n### Response:") tokens = llm2.tokenize(user_message.encode()) count = 0 output = "" outputs = "" for token in llm2.generate(tokens, top_k=50, top_p=0.73, temp=0.72, repeat_penalty=1.1): text = llm2.detokenize([token]) outputs += text.decode() count += 1 if count >= 500 or (token == llm2.token_eos()): break output += text.decode(errors='ignore') yield output gr.HTML("Thanks for checking out this app!") gr.Button("Answer").click( fn=bot, inputs=gr.Textbox(), outputs=gr.Textbox(), ) demo.queue() demo.launch(debug=True)