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@senderle
senderle / hand-modify-pdf.md
Created September 23, 2020 15:03
So you want to modify the text of a PDF by hand

So you want to modify the text of a PDF by hand...

If you, like me, resent every dollar spent on commercial PDF tools, you might want to know how to change the text content of a PDF without having to pay for Adobe Acrobat or another PDF tool. I didn't see an obvious open-source tool that lets you dig into PDF internals, but I did discover a few useful facts about how PDFs are structured that I think may prove useful to others (or myself) in the future. They are recorded here. They are surely not universally applicable --
the PDF standard is truly Byzantine -- but they worked for my case.

@rain-1
rain-1 / LLM.md
Last active July 18, 2024 22:37
LLM Introduction: Learn Language Models

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch
import os
import argparse
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--base_model_name_or_path", type=str)
@younesbelkada
younesbelkada / finetune_llama_v2.py
Last active July 12, 2024 06:54
Fine tune Llama v2 models on Guanaco Dataset
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
@mlabonne
mlabonne / finetune_llama2.py
Last active July 18, 2024 02:12
Easy Llama 2 fine-tuning script (📝 Article: https://tinyurl.com/finetunellama2)
# Based on younesbelkada/finetune_llama_v2.py
# Install the following libraries:
# pip install accelerate==0.21.0 peft==0.4.0 bitsandbytes==0.40.2 transformers==4.31.0 trl==0.4.7 scipy
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from transformers import (