Mxode/SmolLM-Chinese-180M
Text Generation • 0.2B • Updated • 1 • 5
max_stars_repo_path stringlengths 3 269 | max_stars_repo_name stringlengths 4 119 | max_stars_count int64 0 191k | id stringlengths 1 7 | content stringlengths 6 1.05M | score float64 0.23 5.13 | int_score int64 0 5 |
|---|---|---|---|---|---|---|
public_data/serializers.py | MTES-MCT/sparte | 0 | 0 | <reponame>MTES-MCT/sparte
from rest_framework_gis import serializers
from rest_framework import serializers as s
from .models import (
Artificialisee2015to2018,
Artificielle2018,
CommunesSybarval,
CouvertureSol,
EnveloppeUrbaine2018,
Ocsge,
Renaturee2018to2015,
Sybarval,
Voirie2018,... | 2.015625 | 2 |
quick_search/admin.py | naman1901/django-quick-search | 0 | 1 | from django.contrib import admin
from .models import SearchResult
# Register your models here.
class SearchResultAdmin(admin.ModelAdmin):
fields = ["query", "heading", "url", "text"]
admin.site.register(SearchResult, SearchResultAdmin) | 1.640625 | 2 |
rasa/train.py | Amirali-Shirkh/rasa-for-botfront | 0 | 2 | import asyncio
import os
import tempfile
from contextlib import ExitStack
from typing import Text, Optional, List, Union, Dict
from rasa.importers.importer import TrainingDataImporter
from rasa import model
from rasa.model import FingerprintComparisonResult
from rasa.core.domain import Domain
from rasa.utils.common im... | 2.09375 | 2 |
coding_intereview/1475. Final Prices With a Special Discount in a Shop.py | Jahidul007/Python-Bootcamp | 2 | 3 | <gh_stars>1-10
class Solution:
def finalPrices(self, prices: List[int]) -> List[int]:
res = []
for i in range(len(prices)):
for j in range(i+1,len(prices)):
if prices[j]<=prices[i]:
res.append(prices[i]-prices[j])
break
... | 2.765625 | 3 |
rplugin/python3/denite/ui/default.py | timgates42/denite.nvim | 0 | 4 | <gh_stars>0
# ============================================================================
# FILE: default.py
# AUTHOR: <NAME> <<EMAIL> at g<EMAIL>>
# License: MIT license
# ============================================================================
import re
import typing
from denite.util import echo, error, clearm... | 1.882813 | 2 |
PyDSTool/core/context_managers.py | yuanz271/PyDSTool | 0 | 5 | <filename>PyDSTool/core/context_managers.py
# -*- coding: utf-8 -*-
"""Context managers implemented for (mostly) internal use"""
import contextlib
import functools
from io import UnsupportedOperation
import os
import sys
__all__ = ["RedirectStdout", "RedirectStderr"]
@contextlib.contextmanager
def _stdchannel_red... | 2.359375 | 2 |
pos_kiosk/hooks.py | Muzzy73/pos_kiosk | 1 | 6 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from . import __version__ as app_version
app_name = "pos_kiosk"
app_title = "Pos Kiosk"
app_publisher = "9t9it"
app_description = "Kiosk App"
app_icon = "octicon octicon-file-directory"
app_color = "grey"
app_email = "<EMAIL>"
app_license = "MIT"
# Inclu... | 1.414063 | 1 |
pypagai/models/model_lstm.py | gcouti/pypagAI | 1 | 7 | <gh_stars>1-10
from keras import Model, Input
from keras.layers import Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten
from keras.optimizers import Adam
from pypagai.models.base import KerasModel
class SimpleLSTM(KerasModel):
"""
Use a simple lstm neural network
"""... | 2.78125 | 3 |
lib/variables/latent_variables/__init__.py | joelouismarino/variational_rl | 15 | 8 | <filename>lib/variables/latent_variables/__init__.py
from .fully_connected import FullyConnectedLatentVariable
from .convolutional import ConvolutionalLatentVariable
| 1.085938 | 1 |
easyai/model/backbone/cls/pnasnet.py | lpj0822/image_point_cloud_det | 1 | 9 | #!/usr/bin/env python
# -*- coding:utf-8 -*-
# Author:
''' PNASNet in PyTorch.
Paper: Progressive Neural Architecture Search
'''
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.backbone_name import BackboneName
from easyai.model.backbone.utility.base_backbone import *
fr... | 2.71875 | 3 |
map_download/cmd/TerrainDownloader.py | cugxy/map_download | 27 | 10 | # -*- coding: utf-8 -*-
# coding=utf-8
import json
import os
import math
import logging
import requests
import time
from map_download.cmd.BaseDownloader import DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox
def get_access_token(token):
resp = None
request_count = 0
url = "https://ap... | 2.453125 | 2 |
tools/utils.py | vahini01/electoral_rolls | 16 | 11 | <reponame>vahini01/electoral_rolls
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 10 23:28:58 2017
@author: dhingratul
"""
import urllib.request
import os
from selenium import webdriver
from selenium.webdriver.support.ui import Select
from bs4 import BeautifulSoup
import ssl
import requests
impo... | 3 | 3 |
exp/viz_raw_manhattan.py | ellencwade/coronavirus-2020 | 0 | 12 | <gh_stars>0
"""
Experiment summary
------------------
Treat each province/state in a country cases over time
as a vector, do a simple K-Nearest Neighbor between
countries. What country has the most similar trajectory
to a given country?
Plots similar countries
"""
import sys
sys.path.insert(0, '..')
from utils impor... | 3.015625 | 3 |
rational/mxnet/rationals.py | steven-lang/rational_activations | 0 | 13 | <reponame>steven-lang/rational_activations
"""
Rational Activation Functions for MXNET
=======================================
This module allows you to create Rational Neural Networks using Learnable
Rational activation functions with MXNET networks.
"""
import mxnet as mx
from mxnet import initializer
from mxnet.glu... | 2.75 | 3 |
torchflare/criterion/utils.py | Neklaustares-tPtwP/torchflare | 1 | 14 | <filename>torchflare/criterion/utils.py<gh_stars>1-10
"""Utils for criterion."""
import torch
import torch.nn.functional as F
def normalize(x, axis=-1):
"""Performs L2-Norm."""
num = x
denom = torch.norm(x, 2, axis, keepdim=True).expand_as(x) + 1e-12
return num / denom
# Source : https://github.com/... | 2.5625 | 3 |
tests/__init__.py | eloo/sensor.sbahn_munich | 0 | 15 | """Tests for the sbahn_munich integration"""
line_dict = {
"name": "S3",
"color": "#333333",
"text_color": "#444444",
}
| 1.023438 | 1 |
app/views/web/homestack.py | geudrik/hautomation | 0 | 16 | <reponame>geudrik/hautomation
#! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
from flask import Blueprint
from flask import current_app
from flask import render_template
from flask_login import login_required
homestack = Blueprint("homestack", __name__, url_prefix="/homestack")
@homestack.route("/", methods=["... | 2.375 | 2 |
readthedocs/donate/forms.py | gamearming/readthedocs | 0 | 17 | """Forms for RTD donations"""
import logging
from django import forms
from django.conf import settings
from django.utils.translation import ugettext_lazy as _
from readthedocs.payments.forms import StripeModelForm, StripeResourceMixin
from readthedocs.payments.utils import stripe
from .models import Supporter
log ... | 2.359375 | 2 |
pandas_datareaders_unofficial/datareaders/google_finance_options.py | movermeyer/pandas_datareaders_unofficial | 18 | 18 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from .base import DataReaderBase
from ..tools import COL, _get_dates, to_float, to_int
import pandas as pd
#from pandas.tseries.frequencies import to_offset
from six.moves import cStringIO as StringIO
import logging
import traceback
import datetime
import json
import tok... | 2.6875 | 3 |
keras_textclassification/data_preprocess/generator_preprocess.py | Vail-qin/Keras-TextClassification | 1 | 19 | <reponame>Vail-qin/Keras-TextClassification
# !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
from keras_textclassification.data_preprocess.text_preprocess import load_json, save_json
from keras_textclassification.conf.path_config import path_model_dir
path_fast_text... | 2.46875 | 2 |
content/test/gpu/gpu_tests/pixel_expectations.py | metux/chromium-deb | 0 | 20 | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
from gpu_tests.gpu_test_expectations import GpuTestExpectations
# See the GpuTestExpectations class for documentation.
class PixelExpectations(GpuTestExpec... | 1.90625 | 2 |
examples/p02_budgets/budget_data_ingest/migrations/0001_initial.py | 18F/data-federation-ingest | 18 | 21 | <filename>examples/p02_budgets/budget_data_ingest/migrations/0001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.13 on 2018-06-08 22:54
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import dja... | 1.6875 | 2 |
setup.py | Kaslanarian/PythonSVM | 2 | 22 | import setuptools #enables develop
setuptools.setup(
name='pysvm',
version='0.1',
description='PySVM : A NumPy implementation of SVM based on SMO algorithm',
author_email="<EMAIL>",
packages=['pysvm'],
license='MIT License',
long_description=open('README.md', encoding='utf-8').read(),
... | 0.933594 | 1 |
Object_detection_image.py | hiperus0988/pyao | 1 | 23 | <gh_stars>1-10
######## Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and... | 3 | 3 |
polling_stations/apps/data_collection/management/commands/import_torbay.py | chris48s/UK-Polling-Stations | 0 | 24 | from data_collection.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = 'E06000027'
addresses_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv'
stations_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club_... | 1.71875 | 2 |
Backend/product/views.py | Bhavya0020/Readopolis | 0 | 25 | from django.db.models import Q
from django.shortcuts import render
from django.http import Http404
# Create your views here.
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.decorators import api_view
from .models import Product, Category
from .serializers imp... | 2.046875 | 2 |
model/contact.py | hubogeri/python_training | 0 | 26 | from sys import maxsize
class Contact:
def __init__(self, fname=None, mname=None, lname=None, nick=None, title=None, comp=None, addr=None,
home=None, mobile=None, work=None, fax=None, email1=None, email2=None, email3=None,
homepage=None, bday=None, bmonth=None, byear=None, aday=... | 3.109375 | 3 |
test/IECore/BasicPreset.py | ericmehl/cortex | 386 | 27 | ##########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redis... | 1.210938 | 1 |
rlpy/Domains/Pacman.py | imanolarrieta/RL | 1 | 28 | <filename>rlpy/Domains/Pacman.py
"""Pacman game domain."""
from rlpy.Tools import __rlpy_location__
from .Domain import Domain
from .PacmanPackage import layout, pacman, game, ghostAgents
from .PacmanPackage import graphicsDisplay
import numpy as np
from copy import deepcopy
import os
import time
__copyright__ = "Copy... | 2.6875 | 3 |
core/src/zeit/cms/settings/interfaces.py | rickdg/vivi | 5 | 29 | from zeit.cms.i18n import MessageFactory as _
import zope.interface
import zope.schema
class IGlobalSettings(zope.interface.Interface):
"""Global CMS settings."""
default_year = zope.schema.Int(
title=_("Default year"),
min=1900,
max=2100)
default_volume = zope.schema.Int(
... | 2.15625 | 2 |
abc/abc165/abc165e.py | c-yan/atcoder | 1 | 30 | <filename>abc/abc165/abc165e.py
N, M = map(int, input().split())
for i in range(1, M + 1):
if i % 2 == 1:
j = (i - 1) // 2
print(1 + j, M + 1 - j)
else:
j = (i - 2) // 2
print(M + 2 + j, 2 * M + 1 - j)
| 2.953125 | 3 |
setup.py | giggslam/python-messengerbot-sdk | 23 | 31 | <reponame>giggslam/python-messengerbot-sdk<filename>setup.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/lic... | 1.6875 | 2 |
src/transformers/models/mmbt/modeling_mmbt.py | MaximovaIrina/transformers | 1 | 32 | <gh_stars>1-10
# coding=utf-8
# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apac... | 1.820313 | 2 |
eth2/beacon/chains/base.py | mhchia/trinity | 0 | 33 | <filename>eth2/beacon/chains/base.py
from abc import (
ABC,
abstractmethod,
)
import logging
from typing import (
TYPE_CHECKING,
Tuple,
Type,
)
from eth._utils.datatypes import (
Configurable,
)
from eth.db.backends.base import (
BaseAtomicDB,
)
from eth.exceptions import (
BlockNotFoun... | 2.1875 | 2 |
End of preview. Expand in Data Studio
starcoderdata-python-edu
StarCoder Training Dataset Cleaned and Scored
Dataset Details
Dataset Description
This dataset is a filtered version of StarCoder Training Dataset
that has been scored with the python-edu-scorer.
Dataset Sources
- Repository: https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966
- Paper: SmolLM - blazingly fast and remarkably powerful
Citation
@misc{allal2024SmolLM,
title={SmolLM - blazingly fast and remarkably powerful},
author={Loubna Ben Allal and Anton Lozhkov and Elie Bakouch and Leandro von Werra and Thomas Wolf},
year={2024},
}
@article{li2023starcoder,
title={StarCoder: may the source be with you!},
author={Raymond Li and Loubna Ben Allal and Yangtian Zi and Niklas Muennighoff and Denis Kocetkov and Chenghao Mou and Marc Marone and Christopher Akiki and Jia Li and Jenny Chim and Qian Liu and Evgenii Zheltonozhskii and Terry Yue Zhuo and Thomas Wang and Olivier Dehaene and Mishig Davaadorj and Joel Lamy-Poirier and João Monteiro and Oleh Shliazhko and Nicolas Gontier and Nicholas Meade and Armel Zebaze and Ming-Ho Yee and Logesh Kumar Umapathi and Jian Zhu and Benjamin Lipkin and Muhtasham Oblokulov and Zhiruo Wang and Rudra Murthy and Jason Stillerman and Siva Sankalp Patel and Dmitry Abulkhanov and Marco Zocca and Manan Dey and Zhihan Zhang and Nour Fahmy and Urvashi Bhattacharyya and Wenhao Yu and Swayam Singh and Sasha Luccioni and Paulo Villegas and Maxim Kunakov and Fedor Zhdanov and Manuel Romero and Tony Lee and Nadav Timor and Jennifer Ding and Claire Schlesinger and Hailey Schoelkopf and Jan Ebert and Tri Dao and Mayank Mishra and Alex Gu and Jennifer Robinson and Carolyn Jane Anderson and Brendan Dolan-Gavitt and Danish Contractor and Siva Reddy and Daniel Fried and Dzmitry Bahdanau and Yacine Jernite and Carlos Muñoz Ferrandis and Sean Hughes and Thomas Wolf and Arjun Guha and Leandro von Werra and Harm de Vries},
year={2023},
eprint={2305.06161},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
- Downloads last month
- 522
Size of downloaded dataset files:
23.2 GB
Size of the auto-converted Parquet files:
23.2 GB
Number of rows:
12,866,649
Models trained or fine-tuned on jon-tow/starcoderdata-python-edu