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Utkarsh Upadhyay musically-ut

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@vgel
vgel / r1.py
Last active August 14, 2025 13:13
script to run deepseek-r1 with a min-thinking-tokens parameter, replacing </think> with a random continuation string to extend the model's chain of thought
import argparse
import random
import sys
from transformers import AutoModelForCausalLM, AutoTokenizer, DynamicCache
import torch
parser = argparse.ArgumentParser()
parser.add_argument("question", type=str)
parser.add_argument(
@adrienbrault
adrienbrault / llama2-mac-gpu.sh
Last active April 8, 2025 13:49
Run Llama-2-13B-chat locally on your M1/M2 Mac with GPU inference. Uses 10GB RAM. UPDATE: see https://twitter.com/simonw/status/1691495807319674880?s=20
# Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
# Build it
make clean
LLAMA_METAL=1 make
# Download model
export MODEL=llama-2-13b-chat.ggmlv3.q4_0.bin
@VictorTaelin
VictorTaelin / gpt4_abbreviations.md
Last active December 13, 2025 10:50
Notes on the GPT-4 abbreviations tweet

Notes on this tweet.

  • The screenshots were taken on different sessions.

  • The entire sessions are included on the screenshots.

  • I lost the original prompts, so I had to reconstruct them, and still managed to reproduce.

  • The "compressed" version is actually longer! Emojis and abbreviations use more tokens than common words.

@frabert
frabert / COPYING
Last active April 12, 2026 09:37
Favicons for HN
This is free and unencumbered software released into the public domain.
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
@skipcloud
skipcloud / rerere.md
Created February 7, 2020 09:15
Using git's rerere feature to escape recurring conflict hell

Have you ever tried to merge two branches only to end up in conflict hell? You fix a bunch of conflicts only to run git merge --continue and be presented with the same conflicts. Repeat this process and after a few iterations you give up because it just isn't worth the pain and effort.

Would you be surprised to know that there is a git feature specifically for this problem? It's called rerere and I'm going to enrich your life with it now. (I'm going to talk specifically about merging but I think it also helps rebasing)

rerere stands for Reuse Recorded Resolution. The TL;DR version is you ask git to remember how you've resolved hunks in the past, and if the same one comes up for a file in future just redo what you did last time.

To enable this feature just run this lovely command git config --global rerere.enabled true. You can also turn it on by creating this directory in your projects .git/rr-cache, although the global setting is much clearer.

I'll try to take you through an example of how th

@m-aciek
m-aciek / check.py
Created May 10, 2019 22:00
Alembic database freshness check.
from alembic import config
from alembic import script
from alembic.runtime import migration
import sqlalchemy
import exceptions
engine = sqlalchemy.create_engine(DATABASE_URL)
alembic_cfg = config.Config('alembic.ini')
@duhaime
duhaime / headless.py
Last active February 16, 2023 23:19
Python Selenium Headless Chrome OSX
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
chrome_options = Options()
chrome_options.add_argument("--headless")
chrome_options.binary_location = '/Applications/Google Chrome.app/Contents/MacOS/Google Chrome'
driver = webdriver.Chrome(executable_path='/usr/local/bin/chromedriver', chrome_options=chrome_options)
driver.get("http://www.duo.com")
@jnothman
jnothman / bench_semi_supervised_n_iter
Created July 5, 2017 08:24
Benchmarking `sklearn.semi_supervised` `n_iter_` as a function of model and data characteristics
import numpy as np
from sklearn import datasets
from sklearn.semi_supervised import LabelPropagation, LabelSpreading
###for n_samples in [20, 200, 2000, 20000]:
### X, y = datasets.make_classification(n_samples=n_samples, n_classes=3, n_informative=3)
for (X, y) in [datasets.load_iris(return_X_y=True)]:
for model in [LabelPropagation(max_iter=1000),
#LabelSpreading(alpha=0.01),
#LabelSpreading(alpha=0.1),
#LabelSpreading(alpha=0.3)
@musically-ut
musically-ut / update_server.sh
Created March 16, 2017 23:14
Setting up a new server by copying config files from local computer.
#!/bin/bash
set -e
set -u
set -o pipefail
if [ -z $1 ]
then
echo "Usage: $0 [user@]servername"
exit 1