lucataco

from diffusers import DiffusionPipeline
import torch
import time

# load both base & refiner
t1 = time.time()
base = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
)
base.to("cuda")

lucataco

import os
import time
import torch
from typing import Iterator
from threading import Thread
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer

#Change this to 512, 1024, 2048
MAX_NEW_TOKENS = 512
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))

lucataco

import time
import json
import requests


# Start Llama2 13b locally:
# docker run -d -p 5000:5000 --gpus=all r8.im/meta/llama-2-13b@sha256:078d7a002387bd96d93b0302a4c03b3f15824b63104034bfa943c63a8f208c38


url = "http://localhost:5000/predictions"

lucataco

import io
import time
import json
import base64
import requests

# Start SDXL locally:
# docker run -d -p 5000:5000 --gpus=all r8.im/stability-ai/stable-video-diffusion@sha256:3f0457e4619daac51203dedb472816fd4af51f3149fa7a9e0b5ffcf1b8172438

lucataco

import io
import time
import json
import base64
import requests
from PIL import Image
# Start SDXL locally:
# docker run -d -p 5000:5000 --gpus=all r8.im/stability-ai/sdxl@sha256:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b

url = "http://localhost:5000/predictions"

lucataco

from cog import BasePredictor, Input, Path
import os
import torch
import time
from diffusers import (DDIMScheduler, 
    DiffusionPipeline,
    DPMSolverMultistepScheduler,
    EulerAncestralDiscreteScheduler, 
    EulerDiscreteScheduler,
    HeunDiscreteScheduler, 

lucataco

# Update Ubuntu 22.04
sudo apt-get update

# Install cog
sudo curl -o /usr/local/bin/cog -L "https://github.com/replicate/cog/releases/latest/download/cog_$(uname -s)_$(uname -m)"
sudo chmod +x /usr/local/bin/cog

# Install docker
sudo apt install docker-ce
sudo usermod -aG docker $USER

lucataco

import os
import json
import torch
from diffusers import DiffusionPipeline, EulerDiscreteScheduler
from safetensors import safe_open
from dataset_and_utils import TokenEmbeddingsHandler
from safetensors.torch import load_file
from diffusers.models.attention_processor import LoRAAttnProcessor2_0

pipe = DiffusionPipeline.from_pretrained(

lucataco

import os
import torch
from diffusers import DiffusionPipeline, EulerDiscreteScheduler
from safetensors import safe_open
from dataset_and_utils import TokenEmbeddingsHandler

pipe = DiffusionPipeline.from_pretrained(
        "stabilityai/stable-diffusion-xl-base-1.0",
        torch_dtype=torch.float16,
        use_safetensors=True,

lucataco

from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch
import time

model = "tiiuae/falcon-7b"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",