artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since their development in the 1940s, digital computers have been programmed to carry out very complex tasks—such as discovering proofs for mathematical theorems or playing chess—with great proficiency. Despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match full human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in executing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, voice or handwriting recognition, and chatbots.
Pytorch是torch的python版本，是由Facebook开源的神经网络框架，专门针对 GPU 加速的深度神经网络（DNN）编程。Torch 是一个经典的对多维矩阵数据进行操作的张量（tensor ）库，在机器学习和其他数学密集型应用有广泛应用。 Pytorch的计算图是动态的，可以根据计算需要实时改变计算图。 由于Torch语言采用 Lua，导致在国内一直很小众，并逐渐被支持 Python 的 Tensorflow 抢走用户。作为经典机器学习库 Torch 的端口，PyTorch 为 Python 语言使用者提供了舒适的写代码选择。
引入自然语言处理，语音识别模块
https://github.com/Uberi/speech_recognition
Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification.
There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and inference speed relative to the large model; actual speed may vary depending on many factors including the available hardware.
| Size | Parameters | English-only model | Multilingual model | Required VRAM | Relative speed |
|---|---|---|---|---|---|
| tiny | 39 M | tiny.en |
tiny |
~1 GB | ~32x |
| base | 74 M | base.en |
base |
~1 GB | ~16x |
| small | 244 M | small.en |
small |
~2 GB | ~6x |
| medium | 769 M | medium.en |
medium |
~5 GB | ~2x |
| large | 1550 M | N/A | large |
~10 GB | 1x |
pip install -r requirements.txt
pip-compile --upgrade requirements.txt
pip install ddddocr -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install facenet-pytorch
pip install torch torchvision torchaudio
pip install transformers
pip install -r requirements.in
pip install --upgrade pip
python.exe -m pip install --upgrade pip
python manage.py createsuperuser
python manage.py startapp appname
python manage.py syncdb
python manage.py makemigrations
python manage.py migrate --fake
python manage.py migrate --fake-initial
python manage.py migrate --fake
python manage.py clean cache
python manage.py clear_cache --cache defualt # 清理特定缓存
python manage.py clear_cache --all # 清空全部缓存
python manage.py runserver 0.0.0.0
python manage.py dbshell
https://docs.python.org/zh-cn/3.13/library/gc.html
https://docs.djangoproject.com/
https://sourceforge.net/projects/cmusphinx/files/Acoustic%20and%20Language%20Models/Mandarin/
https://github.com/ShenDezhou/Chinese-PreTrained-GPT/tree/main
https://gitcode.com/mirrors/google-bert/bert-base-chinese/tree/main