| # train_grpo.py | |
| import re | |
| import torch | |
| from datasets import load_dataset, Dataset | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| from peft import LoraConfig | |
| from trl import GRPOConfig, GRPOTrainer | |
| # Load and prep dataset |
Just chat.deepseek.com with prompts adapted from this gist.
qX_0 variants, they are actually quite straight-forward so deepseek can come up with a correct result in 1 shot.qX_K it's more complicated, I would say most of the time I need to re-prompt it 4 to 8 more times.q6_K, the code never works until I ask it to only optimize one specific part, while leaving the rest intact (so it does not mess up everything)
Follow these steps to extract all your WhatsApp data, including messages, in a secure and comprehensive way.
This guide is intended to help you access your own data only. Unauthorized access to data that does not belong to you may violate privacy laws and terms of service. Use this guide responsibly.
| """ To use: install Ollama, clone OpenVoice, run this script in the OpenVoice directory | |
| brew install portaudio | |
| brew install git-lfs | |
| git lfs install | |
| git clone https://github.com/myshell-ai/OpenVoice | |
| cd OpenVoice | |
| git clone https://huggingface.co/myshell-ai/OpenVoice | |
| cp -r OpenVoice/* . | |
| """ 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 |
| https://github.com/sergeyprokudin/smplpix | |
| https://github.com/sebastianstarke/AI4Animation | |
| https://github.com/shinework/photoshot | |
| https://github.com/Winfredy/SadTalker | |
| https://github.com/yoyo-nb/Thin-Plate-Spline-Motion-Model | |
| https://github.com/harlanhong/CVPR2022-DaGAN | |
| https://github.com/harlanhong/awesome-talking-head-generation | |
| https://github.com/yerfor/GeneFace | |
| https://github.com/shrubb/latent-pose-reenactment | |
| https://github.com/TheTempAccount/Co-Speech-Motion-Generation |
| //credit - https://huggingface.co/blog/fine-tune-wav2vec2-english (Patrick von Platen) | |
| // run this on your Chrome / Browser Console (where Colab is present) | |
| function ConnectButton(){ | |
| console.log("Connect pushed"); | |
| document.querySelector("#top-toolbar > colab-connect-button").shadowRoot.querySelector("#connect").click() | |
| } | |
| var colab = setInterval(ConnectButton,60000); |
| import argparse | |
| from pdfminer.high_level import extract_text | |
| from sentence_transformers import SentenceTransformer, CrossEncoder, util | |
| from text_generation import Client | |
| PREPROMPT = "Below are a series of dialogues between various people and an AI assistant. The AI tries to be helpful, polite, honest, sophisticated, emotionally aware, and humble-but-knowledgeable. The assistant is happy to help with almost anything, and will do its best to understand exactly what is needed. It also tries to avoid giving false or misleading information, and it caveats when it isn't entirely sure about the right answer. That said, the assistant is practical and really does its best, and doesn't let caution get too much in the way of being useful.\n" | |
| PROMPT = """"Use the following pieces of context to answer the question at the end. | |
| If you don't know the answer, just say that you don't know, don't try to |