sayakpaul

from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained(
    "black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16
).to("cuda")
pipeline.load_lora_weights("sayakpaul/yarn_art_lora_flux", weight_name="pytorch_lora_weights.safetensors")
image = pipeline("a puppy in a pond, yarn art style", guidance_scale=3.5, height=768).images[0]
image.save("yarn.png")

thomwolf

""" To use: install LLM studio (or Ollama), clone OpenVoice, run this script in the OpenVoice directory
    git clone https://github.com/myshell-ai/OpenVoice
    cd OpenVoice
    git clone https://huggingface.co/myshell-ai/OpenVoice
    cp -r OpenVoice/* .
    pip install whisper pynput pyaudio
"""

from openai import OpenAI
import time

danielgross

import requests
import time
import os
import sys
import openai
import tiktoken
from termcolor import colored

openai.api_key = open(os.path.expanduser('~/.openai')).read().strip()

Keno

theogf

using Distributions
using Plots; pyplot()
using ForwardDiff
using LaTeXStrings

λ = 3.0
μ = 2.0
s = 0.8
# α = Exponential(λ) # Measure alpha the starting point
α = Laplace(μ, s + 1.0)

daveluo

EderSantana

dimi-tree

# Working with multiple stocks

"""
SPY is used for reference - it's the market
Normalize by the first day's price to plot on "equal footing"
"""

import os
import pandas as pd
import matplotlib.pyplot as plt

astocko

"""Total Least Squares using PCA"""
# Copyright (c) 2015 Alexander Stocko <[email protected]>
# License: BSD 3 Clause

import numpy as np
import sklearn.decomposition


def tls_ratio(x, y):
    A = np.stack([x, y]).T

bmcfee