app.py

import spaces
import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import subprocess
import os

def install_cuda_toolkit(): #Swiftly Provided by https://huggingface.co/John6666 to fix OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.
    # CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run"
    CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run"
    CUDA_TOOLKIT_FILE = "/tmp/%s" % os.path.basename(CUDA_TOOLKIT_URL)
    subprocess.call(["wget", "-q", CUDA_TOOLKIT_URL, "-O", CUDA_TOOLKIT_FILE])
    subprocess.call(["chmod", "+x", CUDA_TOOLKIT_FILE])
    subprocess.call([CUDA_TOOLKIT_FILE, "--silent", "--toolkit"])

    os.environ["CUDA_HOME"] = "/usr/local/cuda"
    os.environ["PATH"] = "%s/bin:%s" % (os.environ["CUDA_HOME"], os.environ["PATH"])
    os.environ["LD_LIBRARY_PATH"] = "%s/lib:%s" % (
        os.environ["CUDA_HOME"],
        "" if "LD_LIBRARY_PATH" not in os.environ else os.environ["LD_LIBRARY_PATH"],
    )
    # Fix: arch_list[-1] += '+PTX'; IndexError: list index out of range
    os.environ["TORCH_CUDA_ARCH_LIST"] = "8.0;8.6"

install_cuda_toolkit() #Swiftly Provided by https://huggingface.co/John6666 to fix OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.

device = "cuda" if torch.cuda.is_available() else "cpu"

tokenizer = AutoTokenizer.from_pretrained("ISTA-DASLab/Meta-Llama-3.1-70B-AQLM-PV-2Bit-1x16")
model = AutoModelForCausalLM.from_pretrained("ISTA-DASLab/Meta-Llama-3.1-70B-AQLM-PV-2Bit-1x16", torch_dtype='auto', device_map='auto').to(device)

@spaces.GPU
def generate_text(prompt):
    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
    outputs = model.generate(inputs.input_ids) #, max_length=100)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

interface = gr.Interface(
    fn=generate_text,
    inputs="text",
    outputs="text",
    title="Meta-Llama-3.1-70B-AQLM-PV-2Bit-1x16 Text Generation",
    description="Enter a prompt and generate text using Meta-Llama-3.1-70B-AQLM-PV-2Bit-1x16. Responses are a little bit different Meta-Llama-3.1-70B",
)

interface.launch()