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# This is a modified version of TRL's `SFTTrainer` example (https://github.com/huggingface/trl/blob/main/examples/scripts/sft_trainer.py), | |
# adapted to run with DeepSpeed ZeRO-3 and Mistral-7B-V1.0. The settings below were run on 1 node of 8 x A100 (80GB) GPUs. | |
# | |
# Usage: | |
# - Install the latest transformers & accelerate versions: `pip install -U transformers accelerate` | |
# - Install deepspeed: `pip install deepspeed==0.9.5` | |
# - Install TRL from main: pip install git+https://github.com/huggingface/trl.git | |
# - Clone the repo: git clone github.com/huggingface/trl.git | |
# - Copy this Gist into trl/examples/scripts | |
# - Run from root of trl repo with: accelerate launch --config_file=examples/accelerate_configs/deepspeed_zero3.yaml --gradient_accumulation_steps 8 examples/scripts/sft_trainer.py |
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name: Minimal Android CI Workflow | |
on: | |
push: | |
branches: | |
- master | |
tags: | |
- 'v*' | |
jobs: |
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files.download('example.txt') # from colab to browser download |
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import datetime, pytz | |
tz = pytz.timezone('Asia/Bangkok') | |
def now(): | |
now1 = datetime.datetime.now(tz) | |
month_name = 'x มกราคม กุมภาพันธ์ มีนาคม เมษายน พฤษภาคม มิถุนายน กรกฎาคม สิงหาคม กันยายน ตุลาคม พฤศจิกายน ธันวาคม'.split()[now1.month] | |
thai_year = now1.year + 543 | |
time_str = now1.strftime('%H:%M:%S') | |
return "%d %s %d %s"%(now1.day, month_name, thai_year, time_str) # 30 ตุลาคม 2560 20:45:30 |
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# -*- coding: utf-8 -*- | |
from __future__ import absolute_import, unicode_literals, print_function | |
import re | |
try: | |
import icu | |
thkey = icu.Collator.createInstance(icu.Locale('th_TH')).getSortKey | |
except ImportError: | |
def thkey(word): | |
cv = re.sub('[็-์]', '', word) # remove tone |
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from marisa_trie import Trie | |
# wordlist = ... | |
trie = Trie(wordlist) | |
def lmcut(text): | |
for w in reversed(trie.prefixes(text)): | |
if w==text: | |
yield [w] | |
else: |
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import re | |
from collections import defaultdict | |
from marisa_trie import Trie | |
wordlist = [li.strip() for li in open('wordlist.txt')] | |
trie = Trie(wordlist) # สร้างครั้งเดียว ข้างนอก function | |
class LatticeString(str): | |
''' String subclass เพื่อเก็บวิธีตัดหลายๆ วิธี | |
''' |
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# ตาม guru.sanook.com/1520 | |
import re | |
t1 = str.maketrans("กขฃคฅฆงจฉชฌซศษสญยฎดฏตณนฐฑฒถทธบปผพภฝฟมรลฬฤฦวหฮอ", | |
"กกกกกกงจชชชซซซซยยดดตตนนททททททบปพพพฟฟมรรรรรวหหอ") | |
t2 = str.maketrans( | |
"กขฃคฅฆงจฉชซฌฎฏฐฑฒดตถทธศษสญณนรลฬฤฦบปพฟภผฝมำยวไใหฮาๅึืเแโุูอ", | |
"1111112333333333333333333444444445555555667777889AAABCDEEF") | |
def LK82(s): | |
res = [] |
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<?xml version='1.0' encoding='UTF-8'?> | |
<container xmlns="urn:oasis:names:tc:opendocument:xmlns:container" version="1.0"> | |
<rootfiles> | |
<rootfile media-type="application/oebps-package+xml" full-path="content.opf"/> | |
</rootfiles> | |
</container> |
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from keras.models import Sequential | |
from keras.layers.core import Dense, Dropout, Activation | |
from keras.optimizers import SGD | |
import numpy as np | |
X = np.array([[0,0],[0,1],[1,0],[1,1]]) | |
y = np.array([[0],[1],[1],[0]]) | |
model = Sequential() | |
model.add(Dense(8, input_dim=2)) |
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