<Thought> Хорошо, мне нужно объяснить почему трава зеленая. Во-первых, давайте разберемся с основными компонентами фотосинтеза и света. Фотосинтез - это процесс, при котором растения используют свет для преобразования углекислого газа в глюкозу, которая является основным источником энергии для растений. Растения поглощают солнечный свет через хлорофилл, который представляет собой зеленый пигмент, обнаруженный в их клетках. Хлорофиллы имеют тенденцию поглощать синий и красный спектры солнечного излучения более эффективно, чем другие цвета спектра. Однако они также отражают зеленые волны обратно к нашим глазам. Это означает, что мы видим траву как зеленую из-за ее способности отражать преимущественно зеленый цвет. Кроме того, я думаю о том, насколько важен этот аспект для выживания растений. Зеленый цвет помогает им маскироваться среди окружающей среды, а также служит сигналом другим животным или насекомым об источнике пищи. Более того, некоторые виды травы могут иметь р
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# peft_model = AutoPeftModelForCausalLM.from_pretrained(output_dir, device_map={"": "cpu"}).to("cpu") | |
# print(peft_model) | |
PeftModelForCausalLM( | |
(base_model): LoraModel( | |
(model): Qwen2ForCausalLM( | |
(model): Qwen2Model( | |
(embed_tokens): Embedding(151665, 3584, padding_idx=151643) | |
(layers): ModuleList( | |
(0-27): 28 x Qwen2DecoderLayer( | |
(self_attn): Qwen2SdpaAttention( |
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{"problem": "Convert the point $(0,3)$ in rectangular coordinates to polar coordinates. Enter your answer in the form $(r,\\theta),$ where $r > 0$ and $0 \\le \\theta < 2 \\pi.$", "solution": "We have that $r = \\sqrt{0^2 + 3^2} = 3.$ Also, if we draw the line connecting the origin and $(0,3),$ this line makes an angle of $\\frac{\\pi}{2}$ with the positive $x$-axis.\n\n[asy]\nunitsize(0.8 cm);\n\ndraw((-0.5,0)--(3.5,0));\ndraw((0,-0.5)--(0,3.5));\ndraw(arc((0,0),3,0,90),red,Arrow(6));\n\ndot((0,3), red);\nlabel(\"$(0,3)$\", (0,3), W);\ndot((3,0), red);\n[/asy]\n\nTherefore, the polar coordinates are $\\boxed{\\left( 3, \\frac{\\pi}{2} \\right)}.$", "answer": "\\left( 3, \\frac{\\pi}{2} \\right)", "subject": "Precalculus", "level": 2, "unique_id": "test/precalculus/807.json"} | |
{"problem": "Define\n\\[p = \\sum_{k = 1}^\\infty \\frac{1}{k^2} \\quad \\text{and} \\quad q = \\sum_{k = 1}^\\infty \\frac{1}{k^3}.\\]Find a way to write\n\\[\\sum_{j = 1}^\\infty \\sum_{k = 1}^\\infty \\frac{1}{(j + k)^3}\\]in terms |
Напиши код на python который бы реализовывал этот алгоритм:
Algorithm 1 Star Attention - Phase 1: Context Encoding
1:Context c, Block size b
2:L←length(c)
3:Split c into n=⌈L/b⌉ blocks, such that c=\[c1,c2,…,cn\] ▷ Each block has upto b tokens
4:for i=2 to n do
5: ci′←(c1,ci) ▷ Each block ci is prefixed with anchor block c1
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import os | |
import os.path | |
import urllib.parse | |
import zipfile | |
import datetime | |
from selenium import webdriver | |
from selenium.webdriver.firefox.service import Service as FirefoxService | |
from selenium.webdriver.common.by import By | |
from selenium.webdriver.support.ui import WebDriverWait |
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import os | |
import time | |
import re | |
import requests | |
import hashlib | |
import mysql.connector | |
from duckduckgo_search import DDGS | |
from concurrent.futures import ThreadPoolExecutor | |
class HtmlExtractor: |
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# See https://github.com/EvilFreelancer/datasets-translator | |
import torch | |
import json | |
from transformers import T5ForConditionalGeneration, T5Tokenizer, BitsAndBytesConfig | |
from tqdm import tqdm | |
from bs4 import BeautifulSoup, NavigableString | |
# Quantization related settings |
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import os | |
import torch | |
from transformers import GPT2LMHeadModel, GPT2Config, GPT2Tokenizer, pipeline | |
if not os.path.exists("ru_gpts"): | |
raise Exception( | |
"Folder `ru_gpts` not found! Please run `git clone https://github.com/EvilFreelancer/ru-gpts.git ru_gpts` first") | |
from ru_gpts.src.xl_wrapper import RuGPT3XL |
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import requests | |
import json | |
import timeit | |
start = timeit.default_timer() | |
prompt = "С какой периодичностью происходит ледниковый период" | |
result = requests.post('http://localhost:11434/api/generate', json={'model': "llama3.1:70b", "options":{ "seed": 123,"num_predict":500,"temperature": 0,"num_ctx": 4000}, "keep_alive":"10m", "prompt":prompt, "stream": False}).content | |
a = json.loads(result) | |
print( a['response']) | |
print("Всего токенов: ",a['eval_count']) |
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