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reacted to mlabonne's post with ๐Ÿ‘ about 14 hours ago
replied to Dragunflie-420's post 1 day ago
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่ฏดไธๅฆ‚ๅš,ๅฐ่ฏ•ไธ€ไธชไฝ ๆ“…้•ฟ็š„้ข†ๅŸŸ,ๅœจ่ฟ™ไธช้ข†ๅŸŸๅ†…ๅšไธ€ไธชAIไบงๅ“,็„ถๅŽๆŠŠ่ฟ™ไธชๅ–ๅ‡บๅŽป:)

reacted to Dragunflie-420's post with ๐Ÿ‘€ 1 day ago
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2001
Hello community. My name is nikki and I am looking to form a team for a serious project build platform/design/idea/project's...Ive been creating AI professional personas with custom skill sets and divisions of expertise. I want to create a viable business. Ive been working hard but i admit theres so much i do not have time to learn to do. Its taken me three years to learn enough to be here. I dont have a big set up in fact im cloud and ide space trial enterprise here and there all for space. I suck at execution and thats because I dont know how really. I need help from a person. AI has done all it can without hands. Im blabbering at this point. Have nothing big techy to say other than I build and ideate all day hmu glad to meet some like minded individuals ...seriously! Teach me leave me feeling confident in our collaborations not the need to build security software....poor attemt at hacking humor...im neither a comedian or hacker lol....full stacker yep:)
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posted an update 10 days ago
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3553
๐Ÿ˜Š This program is designed to remove emojis from a given text. It uses a regular expression (regex) pattern to match and replace emojis with an empty string, effectively removing them from the text. The pattern includes a range of Unicode characters that correspond to various types of emojis, such as emoticons, symbols, and flags. By using this program, you can clean up text data by removing any emojis that may be present, which can be useful for text processing, analysis, or other applications where emojis are not desired. ๐Ÿ’ป
import re

def remove_emojis(text):
    # Define a broader emoji pattern
    emoji_pattern = re.compile(
        "["
        u"\U0001F600-\U0001F64F"  # emoticons
        u"\U0001F300-\U0001F5FF"  # symbols & pictographs
        u"\U0001F680-\U0001F6FF"  # transport & map symbols
        u"\U0001F1E0-\U0001F1FF"  # flags (iOS)
        u"\U00002702-\U000027B0"
        u"\U000024C2-\U0001F251"
        u"\U0001F900-\U0001F9FF"  # supplemental symbols and pictographs
        u"\U0001FA00-\U0001FA6F"  # chess symbols and more emojis
        u"\U0001FA70-\U0001FAFF"  # more symbols and pictographs
        u"\U00002600-\U000026FF"  # miscellaneous symbols
        u"\U00002B50-\U00002B59"  # additional symbols
        u"\U0000200D"             # zero width joiner
        u"\U0000200C"             # zero width non-joiner
        u"\U0000FE0F"             # emoji variation selector
        "]+", flags=re.UNICODE
    )
    return emoji_pattern.sub(r'', text)
posted an update 13 days ago
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1166
ไธ€ไธชๅŠ ๅ…ฅๆฐดๅฐ็š„ๅฐ็จ‹ๅบ
from PIL import Image, ImageDraw, ImageFont

def add_watermark(image):
    watermark_text = "AI Generated by DarkIdol FeiFei"

    # Ensure the input is an Image object
    if not isinstance(image, Image.Image):
        raise ValueError("Input must be a PIL Image object")

    width, height = image.size

    # Create a drawing object to draw on the image
    draw = ImageDraw.Draw(image)

    # Set the font size for the watermark text
    font_size = 10  # Set font size to 10
    try:
        # Try to use a common font file
        font = ImageFont.truetype("Iansui-Regular.ttf", font_size)
    except IOError:
        # Use the default font if the specified font file is not found
        font = ImageFont.load_default()

    # Calculate the width and height of the watermark text using textbbox
    bbox = draw.textbbox((0, 0), watermark_text, font=font)
    text_width = bbox[2] - bbox[0]
    text_height = bbox[3] - bbox[1]

    # Calculate the position for the watermark text (bottom-right corner)
    x = width - text_width - 10  # 10 is the right margin
    y = height - text_height - 10  # 10 is the bottom margin

    # Add the watermark text to the image
    draw.text((x, y), watermark_text, font=font, fill=(255, 255, 255, 128))

    # Return the modified image object
    return image

- ๅญ—ไฝ“ไปŽhttps://fonts.google.comๅŽปๆ‰พๅฐฑๅฏไปฅไบ†,็จ‹ๅบ้ƒฝๆ ‡ๆณจๆธ…ๆฅšไบ†,่‡ช่กŒไฟฎๆ”น
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reacted to m-ric's post with ๐Ÿ‘ 3 months ago
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2578
๐‡๐ฎ๐ ๐ ๐ข๐ง๐  ๐…๐š๐œ๐ž ๐ซ๐ž๐ฅ๐ž๐š๐ฌ๐ž๐ฌ ๐๐ข๐œ๐จ๐ญ๐ซ๐จ๐ง, ๐š ๐ฆ๐ข๐œ๐ซ๐จ๐ฌ๐œ๐จ๐ฉ๐ข๐œ ๐ฅ๐ข๐› ๐ญ๐ก๐š๐ญ ๐ฌ๐จ๐ฅ๐ฏ๐ž๐ฌ ๐‹๐‹๐Œ ๐ญ๐ซ๐š๐ข๐ง๐ข๐ง๐  ๐Ÿ’๐ƒ ๐ฉ๐š๐ซ๐š๐ฅ๐ฅ๐ž๐ฅ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง ๐Ÿฅณ

๐Ÿ•ฐ๏ธ Llama-3.1-405B took 39 million GPU-hours to train, i.e. about 4.5 thousand years.

๐Ÿ‘ด๐Ÿป If they had needed all this time, we would have GPU stories from the time of Pharaoh ๐“‚€: "Alas, Lord of Two Lands, the shipment of counting-stones arriving from Cathay was lost to pirates, this shall delay the building of your computing temple by many moons "

๐Ÿ› ๏ธ But instead, they just parallelized the training on 24k H100s, which made it take just a few months.
This required parallelizing across 4 dimensions: data, tensor, context, pipeline.
And it is infamously hard to do, making for bloated code repos that hold together only by magic.

๐Ÿค ๐—•๐˜‚๐˜ ๐—ป๐—ผ๐˜„ ๐˜„๐—ฒ ๐—ฑ๐—ผ๐—ป'๐˜ ๐—ป๐—ฒ๐—ฒ๐—ฑ ๐—ต๐˜‚๐—ด๐—ฒ ๐—ฟ๐—ฒ๐—ฝ๐—ผ๐˜€ ๐—ฎ๐—ป๐˜†๐—บ๐—ผ๐—ฟ๐—ฒ! Instead of building mega-training codes, Hugging Face colleagues cooked in the other direction, towards tiny 4D parallelism libs. A team has built Nanotron, already widely used in industry.
And now a team releases Picotron, a radical approach to code 4D Parallelism in just a few hundred lines of code, a real engineering prowess, making it much easier to understand what's actually happening!

โšก ๐—œ๐˜'๐˜€ ๐˜๐—ถ๐—ป๐˜†, ๐˜†๐—ฒ๐˜ ๐—ฝ๐—ผ๐˜„๐—ฒ๐—ฟ๐—ณ๐˜‚๐—น:
Counting in MFU (Model FLOPs Utilization, how much the model actually uses all the compute potential), this lib reaches ~50% on SmolLM-1.7B model with 8 H100 GPUs, which is really close to what huge libs would reach. (Caution: the team is leading further benchmarks to verify this)

Go take a look ๐Ÿ‘‰ https://github.com/huggingface/picotron/tree/main/picotron
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