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Create a Lakehouse and then open a Fabric notebook. Attach the Lakehouse that you created to the notebook and run the following code to add all tables to your Lakehouse. Note that you will be using the AdventureWorks dataset which includes retail data with tables for sal...
"import numpy as np\n", "import math\n", "from tqdm.notebook import tqdm\n", "from typing import Tuple, List, Optional, Dict, Callable\n", "from jaxtyping import Float, Int\n", "from transformers.models.gpt2.tokenization_gpt2_fast import GPT2TokenizerFast\n", "from collections impo...
" from .autonotebook import tqdm as notebook_tqdm\n" ] } ], "source": [ "import json\n", "import torch\n", "from transformers import AutoTokenizer, AutoModelForCausalLM\n", "from configuration_minicpm import MiniCPMConfig\n", "from MiniCPM import MiniCPMForCausalLM\n", "import lo...
ui import WebDriverWait from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.common.by import By from selenium.webdriver.chrome.options import Options from tqdm import tqdm_notebook base_url = "https://trustpilot.com" def get_soup(url): return BeautifulSoup(...
fromimportlib.metadataimportversionpkgs=["matplotlib",# Plotting library"tiktoken",# Tokenizer"torch",# Deep learning library"tqdm",# Progress bar"tensorflow",# For OpenAI's pretrained weights]forpinpkgs:print(f"{p} version: {version(p)}")matplotlibversion:3.7.1tiktokenversion:0.7.0torchversion...
intelpython_full packageconda create -n<env name>intelpython3_full#Activate the newly created environmentconda activate<env name># Install Intel AI Kit for Tensorflowcondainstallintel-aikit-tensorflow# Install/Upgrade additional packagespipinstallipykernel pandas matplotlib plotly glob tqdm ...
全文代码主要是以 jupyter notebook 的形式展开的,并不是.py文件的形式,也就是说前面执行的变量会在中间储存下来。 这次除了 torch,用到的库有: transformers peft datasets accelearate tqdm einops 具体可以见仓库的requirements.txt。 这次的代码和上一次文章的代码整合到一起,放在这里:Mxoder/LLM-from-scratch。
from tqdm import tqdm import numpy as onp onp.random.seed(0) test_idxes = onp.random.randint(0, len(X_test), 1000) #Record messages over test dataset here: newtestloader = DataLoader( [Data( X_test[i], edge_index=edge_index, ...
(config, video, videotype, shuffle, trainingsetindex, filtertype, windowlength, p_bound, ARdegree, MAdegree, alpha, save_as_csv, destfolder) 108 Dataframe = pd.read_hdf(sourcedataname,'df_with_missing') 109 for bpindex,bp in tqdm(enumerate(cfg['bodyparts'])): --> 110 pdindex = ...