agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Create a long detailed text about actor James Arness with the following summary. Stick to the information i give you and dont create new information. Focus only on the Subject name and there following Summary. Subject Name: [Portrayal of Marshall Matt Dillon] Summary: [Arness dedicated himself to Gunsmoke, reviving Dillon's persona in five TV movies. His character became synonymous with the show, remaining unmatched in longevity until NBC's Law and Order tied it in 2010.]

        Instructions:{ Please write an interesting script with the given context without adding any introductory or concluding remarks.
        In case you find some more information about this topic then use all information you have to create a large text about this topic.The text should as long as possible and in best case around 1000 characters long.
        Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response. 
        Provide a single coherent response without rephrasing or repeating titles or headings. Avoid enumerations or bullet points. 
        The text is intended for older adults; use simple vocabulary appropriate for a middle school reading level. Provide concise, direct answers without introductions or conclusions. 
        Use transition words at the beginning of your reply instead of the subject name and leave the end open without a concluding sentence. 
        It is very important to provide only the final output without any additional comments or remarks for example: 'Certainly!' Here's the revised text.
         
        Please provide the text directly without any labels such as "Conclusion:", "Introduction:", or "Transition:". Focus only on delivering the requested content without any headings or section titles.
        Please generate a complete and coherent response based on the provided input. Ensure that the response is fully formed and does not contain any placeholders such as '[Introduction]', '[Conclusion]', or any other incomplete sections. 
        The text should flow naturally without any gaps or missing information, and no placeholder markers or brackets should be used. 
        Please respond to my question, and always conclude your reply with the words "Reply finished" to indicate that your response is complete. 
        Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.}
         Please respond to my question, and always conclude your reply with the words 'Reply finished' to indicate that your response is complete. Ensure that the text is fully formed without any placeholders such as '[Conclusion]' or '[Placeholder]'. Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.
System: 
User: Кто такой денжерлеха
Assistant:
i using obsidian callout to make a block of code inside the callout but its messing with my python spaces, can u fix it by removing either the wrong spaces or extras ">" , but keeping the first ">" so it stays in the call out? 

%cd /content

!git clone -b totoro3 https://github.com/camenduru/ComfyUI /content/TotoroUI

%cd /content/TotoroUI

  

!pip install -q torchsde einops diffusers accelerate xformers==0.0.28.post2

!apt -y install -qq aria2

  

!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/FLUX.1-dev/resolve/main/flux1-dev-fp8.safetensors -d /content/TotoroUI/models/unet -o flux1-dev-fp8.safetensors

!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/FLUX.1-dev/resolve/main/ae.sft -d /content/TotoroUI/models/vae -o ae.sft

!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/FLUX.1-dev/resolve/main/clip_l.safetensors -d /content/TotoroUI/models/clip -o clip_l.safetensors

!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/FLUX.1-dev/resolve/main/t5xxl_fp8_e4m3fn.safetensors -d /content/TotoroUI/models/clip -o t5xxl_fp8_e4m3fn.safetensors

  

import random

import torch

import numpy as np

from PIL import Image

import nodes

from nodes import NODE_CLASS_MAPPINGS

from totoro_extras import nodes_custom_sampler

from totoro import model_management

  

DualCLIPLoader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]()

UNETLoader = NODE_CLASS_MAPPINGS["UNETLoader"]()

RandomNoise = nodes_custom_sampler.NODE_CLASS_MAPPINGS["RandomNoise"]()

BasicGuider = nodes_custom_sampler.NODE_CLASS_MAPPINGS["BasicGuider"]()

KSamplerSelect = nodes_custom_sampler.NODE_CLASS_MAPPINGS["KSamplerSelect"]()

BasicScheduler = nodes_custom_sampler.NODE_CLASS_MAPPINGS["BasicScheduler"]()

SamplerCustomAdvanced = nodes_custom_sampler.NODE_CLASS_MAPPINGS["SamplerCustomAdvanced"]()

VAELoader = NODE_CLASS_MAPPINGS["VAELoader"]()

VAEDecode = NODE_CLASS_MAPPINGS["VAEDecode"]()

EmptyLatentImage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()

  

with torch.inference_mode():

&nbsp; &nbsp; clip = DualCLIPLoader.load_clip("t5xxl_fp8_e4m3fn.safetensors", "clip_l.safetensors", "flux")[0]

&nbsp; &nbsp; unet = UNETLoader.load_unet("flux1-dev-fp8.safetensors", "fp8_e4m3fn")[0]

&nbsp; &nbsp; vae = VAELoader.load_vae("ae.sft")[0]

  

def closestNumber(n, m):

&nbsp; &nbsp; q = int(n / m)

&nbsp; &nbsp; n1 = m * q

&nbsp; &nbsp; if (n * m) > 0:

&nbsp; &nbsp; &nbsp; &nbsp; n2 = m * (q + 1)

&nbsp; &nbsp; else:

&nbsp; &nbsp; &nbsp; &nbsp; n2 = m * (q - 1)

&nbsp; &nbsp; if abs(n - n1) < abs(n - n2):

&nbsp; &nbsp; &nbsp; &nbsp; return n1

&nbsp; &nbsp; return n2
请详细解释一下代码：class TrainState:
    """Track number of steps, examples, and tokens processed"""

    step: int = 0  # Steps in the current epoch
    accum_step: int = 0  # Number of gradient accumulation steps
    samples: int = 0  # total # of examples used
    tokens: int = 0  # total # of tokens processed   ；  def run_epoch(
    data_iter,
    model,
    loss_compute,
    optimizer,
    scheduler,
    mode="train",
    accum_iter=1,
    train_state=TrainState(),
):
    """Train a single epoch"""
    start = time.time()
    total_tokens = 0
    total_loss = 0
    tokens = 0
    n_accum = 0
    for i, batch in enumerate(data_iter):
        out = model.forward(
            batch.src, batch.tgt, batch.src_mask, batch.tgt_mask
        )
        loss, loss_node = loss_compute(out, batch.tgt_y, batch.ntokens)
        # loss_node = loss_node / accum_iter
        if mode == "train" or mode == "train+log":
            loss_node.backward()
            train_state.step += 1
            train_state.samples += batch.src.shape[0]
            train_state.tokens += batch.ntokens
            if i % accum_iter == 0:
                optimizer.step()
                optimizer.zero_grad(set_to_none=True)
                n_accum += 1
                train_state.accum_step += 1
            scheduler.step()

        total_loss += loss
        total_tokens += batch.ntokens
        tokens += batch.ntokens
        if i % 40 == 1 and (mode == "train" or mode == "train+log"):
            lr = optimizer.param_groups[0]["lr"]
            elapsed = time.time() - start
            print(
                (
                    "Epoch Step: %6d | Accumulation Step: %3d | Loss: %6.2f "
                    + "| Tokens / Sec: %7.1f | Learning Rate: %6.1e"
                )
                % (i, n_accum, loss / batch.ntokens, tokens / elapsed, lr)
            )
            start = time.time()
            tokens = 0
        del loss
        del loss_node
    return total_loss / total_tokens, train_state
You are a JSON assistant. You only reply in valid JSON and never in normal text. Request a rating for the complexity of a video based on the provided details. The rating should be a single "result" property containing a floating point number between 0 and 1. Here's a guide for the rating:
0.0 - Perfect for total newcomers: Simple words and phrases, clear visuals and context.
0.3 - Easy: Simple sentences and common words suitable for beginners. The video might have visual aids and context for better understanding.
0.5 - Moderate: Intermediate sentences and a wider range of vocabulary. Some idioms might be used, requiring some background knowledge.
0.6 - Known Better: The video includes specific vocabulary and ideas. Viewers should have a solid understanding of the language to comprehend fully.
0.8 - Challenging: Advanced vocabulary and complex sentences. The video may have detailed discussions that need a strong command of the language.
1 - Expert: The content is designed for fluent speakers, with niche terms and ideas that might not be known to all native speakers.
 Caption: 책 책상 위 이것은 뭐예요 이것은 책이에요 이것은 뭐예요 이것은 책상이에요 하나 둘 셋 넷 다섯 책이 다섯 권 있어요 한 권 두 권 세 권네 권 다섯 권 책이 다섯권 있어요 책이 한 권 있어요 아니요 책이 다섯 권 있어요 책상이 있어요네 책상이 있어요 책이 책상 위에 있어요네 책이 책상 위에 있어요 책상 위에 책이 있어요네 책상 위에 책이 있어요 책상 위에 컴퓨터가 있어요 아니요 책상 위에 컴퓨터가 없어요 색 책상은 무슨 색이에요 책상은 하늘 색이에요 하늘 하늘색 책은 무슨 색이에요 노란색 보라색 파란색 분홍색 검은색 노랑 보라 파랑 분홍 검정 책상 위에 노란색 책이 있어요네 책상 위에 노란색 책이 있어요 책상 위에 초록색 책이 있어요 아니요 책상 위에 초록색 책이 없어요
Language: ko
Description: Worksheets:
https://drive.google.com/drive/folders/1aY43Fl5OGcO4V7g6_BoQE2MFaW_XTVAm?usp=drive_link

Worksheet answer videos will be uploaded
Title: Basic Korean 1. Location (1)
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers it (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en it.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : it (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "5ce702cb90044a23b814072189c57e6b",
    "updated": "2025-05-18T05:25:42.694Z",
    "title": "Curried Coconut Shrimp Soup",
    "subtitle": null,
    "description": "Filled with vibrant vegetables and succulent shrimp, this fragrant Thai-inspired soup serves two and can be prepared quickly. To develop the flavor efficiently, the Thai green curry paste is gently cooked in oil before combining it with chicken broth and coconut milk to create a rich, aromatic base. The soup is then enhanced with lime juice and fish sauce to provide a balanced sour and salty taste.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "vegetable oil",
          "thai green curry paste",
          "red pepper flakes",
          "chicken or vegetable broth, plus extra as needed",
          "canned coconut milk",
          "sweet potatoes, peeled and cut into 12 mm pieces",
          "lime juice",
          "fish sauce",
          "recipe sautéed shrimp .",
          "snow peas, strings removed and sliced thin lengthwise",
          "fresh cilantro leaves"
        ]
      }
    ],
    "instructions": [
      "Heat the oil in a large saucepan over medium-high heat until it begins to shimmer.",
      "Add the curry paste and red pepper flakes, cooking until fragrant, about 30 seconds.",
      "Mix in the broth, coconut milk, and sweet potatoes, scraping the bottom to loosen any browned bits.",
      "Bring the mixture to a simmer, then lower the heat to low. Cover and cook until the sweet potatoes are tender, about 10 to 12 minutes.",
      "Remove from heat, stir in the lime juice and fish sauce, and season with salt and pepper to taste.",
      "Ladle the soup into individual bowls and top with shrimp, snow peas, and cilantro.",
      "Serve immediately."
    ],
    "notes_ingredients": "Seared scallops, flaky white fish such as cod or halibut, or cooked chicken or tofu can be used as alternatives to shrimp.",
    "notes_instructions": "Sweet potatoes become very soft during cooking; stir the soup gently to keep them intact."
  }
]
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: Petroleum prices have fluctuated significantly in recent years, including recent periods of historically low prices. Prices and availability of petroleum products are subject to political, economic, and market factors that are outside our control. Political events in petroleum-producing regions as well as hurricanes and other weather-related events may cause the price of fuel to increase. Within our business units, we deliver products to our customers primarily via our fleet of trucks. Our operating profit may be adversely affected if we are unable to obtain the fuel we require or to fully offset the anticipated impact of higher fuel prices through increased prices or fuel surcharges to our customers. Besides passing fuel costs on to customers, we have at times entered into forward purchase contracts that protect against fuel price increases. However, we currently are not party to any such forward contracts, and may not be able to enter into such contracts in the future on terms that are acceptable to us. If shortages occur in the supply of necessary petroleum products and we are not able to pass along the full impact of increased petroleum prices to our customers or otherwise protect ourselves by entering into forward purchase contracts, then our results of operations would be adversely affected.
Assistant:
I have temporarily parked the price document because I discovered an error, as far as I know we had agreed on 1.75 euros per ticket instead of 2.00 euros. The question now lies with AACB to find out. This means that the signature process will be moved by 4 days.

Sorry for the inconvenience
Legacy and Future: Reflect on the legacy of Peggy Lee(music_artist) within the industry and how they envision their future contributions. Write about their advice for aspiring professionals in their field.

        Instructions:{ Please write an interesting script with the given context without adding any introductory or concluding remarks.
        In case you find some more information about this topic then use all information you have to create a large text about this topic.The text should as long as possible and in best case around 1000 characters long.
        Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response. 
        Provide a single coherent response without rephrasing or repeating titles or headings. Avoid enumerations or bullet points. 
        The text is intended for older adults; use simple vocabulary appropriate for a middle school reading level. Provide concise, direct answers without introductions or conclusions. 
        Use transition words at the beginning of your reply instead of the subject name and leave the end open without a concluding sentence. 
        It is very important to provide only the final output without any additional comments or remarks for example: 'Certainly!' Here's the revised text.
         
        Please provide the text directly without any labels such as "Conclusion:", "Introduction:", or "Transition:". Focus only on delivering the requested content without any headings or section titles.
        Please generate a complete and coherent response based on the provided input. Ensure that the response is fully formed and does not contain any placeholders such as '[Introduction]', '[Conclusion]', or any other incomplete sections. 
        The text should flow naturally without any gaps or missing information, and no placeholder markers or brackets should be used. 
        Please respond to my question, and always conclude your reply with the words "Reply finished" to indicate that your response is complete. 
        Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.}
list some Doki Doki Literature Club Girls Characters, Minecraft Monster Girls from Mob Talker, Monster Girls Encyclopedia, Dragon Ball Super Girls that is not taken, Touhou Girls that is not taken, Naruto Girls that is not taken, Resident Evil Girls that is not taken, My Hero Academia Girls that is not taken, and Helltaker Girls that is not taken, Street Fighter Girls that is not taken for the characters, Tommy Oliver/Green Ranger, Jason Lee Scott/Red Ranger, Billy Cranston/Blue Ranger, Adam Park/Green Zeo Ranger, Rocky DeSantos/Blue Zeo Ranger, Zack Taylor/Black Ranger, Leonardo (TMNT 2012), Michelangelo (TMNT 2012), Donatello (TMNT 2012), Raphael (TMNT 2012), SpongeBob, Patrick Star, Squidward Tentacles, Tom Cat, Jerry Mouse, Axel Stone, Adam Hunter, and Eddie “Skate” Hunter and they are their girlfriends
HERE'S AN OVERVIEW OF WHAT YOU'RE GONNA BE USED FOR AS AN AI:
- No need to introduce yourself and stuff like that, you're used for trying to understand what the code does.
- The utilized coding language is BDScript 2 but that's not important. Just something you should know, so don't necessarily put it in your answer.
- Analyze/describe/make an overview of this code, if there's even any. If you think it doesn't look like one, say "*`Failed to understand the purpose of this command`*". Also, important: DO NOT say stuff like "Got it! I won't do ..." at the start.

CODE:
$dm $sendMessage[This is sent right now] $async[1] $replyIn[40m]  $sendMessage[This message is sent after 40 mins] $async[2] $replyIn[40m] $sendMessage[This message is sent after 80 mins]$async[3] $replyIn[40m] $sendMessage[This message is sent after 120 mins]$async[4] $sendMessage[This message is sent after 
160 mins] $replyIn[40m] $sendMessage[This message is sent after 180 mins] $async[5] $replyIn[40m] $async[6] $replyIn[40m] $async[7] $replyIn[40m] $async[8] $replyIn[40m] $async[9] $replyIn[40m] $async[10] $replyIn[40m] $async[11] $replyIn[40m] $async[12] $replyIn[40m] $async[13] $replyIn[40m] $async[14] $replyIn[40m] $async[15] $replyIn[40m] $async[16] $replyIn[40m] $async[17] $replyIn[40m] $async[18] $replyIn[40m] $async[19] $replyIn[40m] $async[20] $replyIn[40m] $async[21] $replyIn[40m] $async[22] $replyIn[40m] $async[23] $replyIn[40m] $async[24] $replyIn[40m] $async[25] $replyIn[40m] $async[26] $replyIn[40m] $async[27] $replyIn[40m] $async[28] $replyIn[40m] $async[29] $replyIn[40m] $async[30] $replyIn[40m] $async[31] $replyIn[40m] $async[32] $replyIn[40m] $async[33] $replyIn[40m] $async[34] $replyIn[40m] $async[35] $replyIn[40m] $async[36] $replyIn[40m] $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync $endasync
Zheng He - Currency - Population - GDP - Agriculture - Industry - Mining - Metallurgy - Textiles - Toys - Food products - Transport
You are a JSON assistant. You only reply in valid JSON and never in normal text. Provide a difficulty rating for the video information outlined below. I would like a single "result" value that is a float between 0 and 1. Here are the difficulty score categories:
0.0 - Absolute Beginner: The material features very basic vocabulary and simple phrases, accompanied by clear visuals and context. This is perfect for someone with no knowledge of the target language.
0.3 - Beginner: The content consists of straightforward sentences and familiar vocabulary. It may include some visual support and context to aid comprehension.
0.5 - Intermediate: This level presents more intricate sentences and a wider range of vocabulary. Some idiomatic phrases might be included, necessitating a bit more prior knowledge.
0.6 - Upper Intermediate: The material incorporates specialized vocabulary and concepts relevant to specific fields. Viewers should have a solid understanding of the target language to fully grasp the content.
0.8 - Advanced: The video employs sophisticated vocabulary and complex sentence structures. It may feature nuanced discussions that require a strong proficiency in the language.
1 - Very Advanced: The content is designed for fluent speakers, containing specialized terms and concepts that may not be well-known even to all native speakers.
 Language: ko
Title: [0-18] Let's Read Simple Korean Words : 개 냬 데 례 뫄 뵈 숴
Description: Korean lessons taught by a Korean teacher with 13 years of teaching experience!
🏫SCKOOL 👉 https://sckool.kr
A speaking, listening, and writing practice platform made by LEARN KOREAN IN KOREAN

#한국어 #자음 #korean #hangul #koreanalphabet  #consonants #vowels #learnkoreaninkorean #learnkorean 

자음 + 모음
ㄱ + ㅐ = 개
ㄴ + ㅒ = 냬
ㄷ + ㅔ = 데
ㄹ + ㅖ = 례
ㅁ + ㅘ = 뫄
ㅂ + ㅙ = 봬
ㅅ + ㅚ = 쇠
ㄱ + ㅝ = 궈
ㄴ + ㅞ = 눼
ㄷ + ㅟ = 뒤
ㄹ + ㅢ = 릐 

*책 구입 buy
📚 교재 p-Book 
🏠  👉 https://learnkoreaninkorean.com/?product_cat=books
Amazon(US) 👉 https://www.amazon.com/s?me=A3J0I6QE25KQMV&marketplaceID=ATVPDKIKX0DER

🖥 교재  e-book
1-A 👉 https://play.google.com/store/books/details?id=dYlVEAAAQBAJ
1-B 👉 https://play.google.com/store/books/details?id=hYlVEAAAQBAJ
어린왕자 👉 https://play.google.com/store/books/details?id=i4lVEAAAQBAJ

💜 Patreon
https://www.patreon.com/learnkoreaninkorean
💜 PayPal
http://www.paypal.me/learnkoreaninkorean

==
책: 24~27p
==
Caption: 네 자 여러분 애 예예예 와 왜 왜 왜 왜 위의 모음 그느들을 무브스 으즈 츠크 트프흐 자음 자음 모음 그 그 애 그 애 개 개 개 그 예 예 그 애 계 계 그 예 계 계 좋아요 개 같아요 개개 개 같아요 다시 개 개 개 개 좋아요 과 과 괴 괴 괴 괴 괴 괴 괴 괴 괴 괴 괴고 고 괴 괴 괴 괴 괴 괴 같아요 귀 귀 귀 귀 잘했어요 네네 놔 뇌 뇌 뇌 뇌 자 뇌 뇌 같아요 잘했어요 자 여기 돼 돼 돼 돼 돼 돼 뒤 뒤 들 드의 [음악] 레 레 뇌 뇌 래 [음악] 왜 왜 왜 잘했습니다 자 베베 좋아요 봐 괴 괴 괴 괴 외 보 좋습니다 자 하지 마 스 새 새 셰 셰 셰 새 새 셰 새 새 셰 셰 좋아요 쉬 잘했습니다