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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)
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
@ssghost
ssghost / main.ipynb
Last active February 15, 2025 06:34
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@ssghost
ssghost / get_memory_size.py
Created January 20, 2025 11:23 — forked from philschmid/get_memory_size.py
Get needed GPU per precision for a Hugging Face Model Id
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] = {
@ssghost
ssghost / phi-4-unsloth-notebook.ipynb
Created January 17, 2025 08:17
Phi-4 Unsloth notebook
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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
<!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;
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)
})?;
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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