| from diffusers import FluxPipeline, AutoencoderKL | |
| from diffusers.image_processor import VaeImageProcessor | |
| from transformers import T5EncoderModel, T5TokenizerFast, CLIPTokenizer, CLIPTextModel | |
| import torch | |
| import gc | |
| def flush(): | |
| gc.collect() | |
| torch.cuda.empty_cache() |
| from diffusers import StableDiffusion3Pipeline | |
| from transformers import T5EncoderModel | |
| import torch | |
| import time | |
| import gc | |
| def flush(): | |
| gc.collect() | |
| torch.cuda.empty_cache() |
A step-by-step guide to deploying web applications (using HTML, CSS, JavaScript) on GitHub Pages, categorized into three main sections for ease of understanding and implementation.
Create Your Web Application
index.html file.Organize Your Application
| import chess | |
| import re | |
| import outlines.text.generate as generate | |
| import outlines.models as models | |
| import chess.engine | |
| import chessboard.display | |
| import os | |
| os.environ["TOKENIZERS_PARALLELISM"] = "false" |
| { | |
| "last_node_id": 25, | |
| "last_link_id": 41, | |
| "nodes": [ | |
| { | |
| "id": 4, | |
| "type": "Width/Height Literal", | |
| "pos": [ | |
| -209, | |
| 451 |
| ''' This script uses ytmusicapi and pytube together to download your playlists, history or 'liked' songs as | |
| high-quality audio-only streams from Youtube Music, which are protected by a "signatureCipher" obfuscation scheme. | |
| To use it, first install [ytmusicapi] and [pytube] using pip, then follow the instructions for creating the auth | |
| file from the response in an authenticated session to a watch-page request as found in your browser's dev-tools. | |
| The downloaded files are placed in ~/Music, named with the artist and track metadata, and will be skipped instead | |
| of downloaded again next time it is run, based on the videoIds of the downloaded songs. | |
| Merry Xmas - V. |
| # 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 |
| mp=1; size=7B; # to run 7B | |
| mp=8; size=65B; # to run 65B | |
| for seed in $(randint 1000000) | |
| do | |
| export TARGET_FOLDER=~/ml/data/llama/LLaMA | |
| time python3 -m torch.distributed.run --nproc_per_node $mp example.py --ckpt_dir $TARGET_FOLDER/$size --tokenizer_path $TARGET_FOLDER/tokenizer.model --seed $seed --max_seq_len 2048 --max_gen_len 2048 --count 0 | tee -a ${size}_startrek.txt | |
| done |
| { | |
| "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json", | |
| "basics": { | |
| "name": "Stéphane BUSSO", | |
| "label": "Tech Leader | Architect | Developer | Web3 | Blockchain | SaaS", | |
| "image": "", | |
| "email": "[email protected]", | |
| "phone": "+642108923834", | |
| "summary": "As an experienced engineering manager and technical leader, I enjoy helping companies grow their teams, design and develop better software solutions, be agile, and deliver quality products and services faster.", | |
| "location": { |