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import pandas as pd | |
from dateutil import parser | |
import plotly.express as px | |
df1 = pd.read_csv("./monthly_job_applications_2025-04-15T08_01_46.84848Z.csv") | |
df2 = pd.read_csv("./monthly_job_posts_2025-04-15T08_01_39.691275Z.csv") | |
df1.rename(columns={"Created At": "Month"}, inplace = True) | |
df2.rename(columns={"Published At": "Month"}, inplace = True) |
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on run {input, parameters} | |
do shell script "nohup /usr/local/bin/llama-server -m '/Volumes/TOSHIBA EXT/GGUF/gemma-3-4b-it-q4_0.gguf' --port 11234 >/dev/null 2>&1 &" | |
return input | |
end run |
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from typing import Dict, Union | |
from huggingface_hub import get_safetensors_metadata | |
import argparse | |
import sys | |
# Example: | |
# python get_gpu_memory.py Qwen/Qwen2.5-7B-Instruct | |
# Dictionary mapping dtype strings to their byte sizes | |
bytes_per_dtype: Dict[str, float] = { |
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def gauss_elim(m: List[List[float]], eps: float = 1.0/(10**10)) -> bool: | |
(h, w) = (len(m), len(m[0])) | |
for i in range(h): | |
maxrow = i | |
for j in range(i+1, h): | |
if abs(m[j][i]) > abs(m[maxrow][i]): | |
maxrow = j | |
(m[i], m[maxrow]) = (m[maxrow], m[i]) | |
if abs(m[i][i]) <= eps: | |
return False |
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<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="UTF-8" /> | |
<link rel="icon" type="image/svg+xml" href="/vite.svg" /> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0" /> | |
<title>Vite App</title> | |
<style> | |
body { | |
padding: 1rem; |
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use mlua::{IntoLua, Lua, Value}; | |
fn main() -> Result<(), Box<dyn std::error::Error>> { | |
let lua = Lua::new(); | |
let utils = lua.create_table()?; | |
let double_fn = lua.create_function(|lua: &Lua, arg_0: i64| { | |
let res = arg_0 * 2; | |
res.into_lua(lua) | |
})?; |
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import asyncio | |
import base64 | |
import json | |
import os | |
import pyaudio | |
from websockets.asyncio.client import connect | |
class SimpleGeminiVoice: | |
def __init__(self): |
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