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README.md

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-Edit this `README.md` markdown file to author your organization card.
+Welcome to join our family to learn together and promote the advancement of machine learning in China!
+Now, let's start
+{
+  1. If you don't have a high-performance GPU, I recommend that you rent one.
+     There are cheap GPUs available for students on the Internet,and some are even free.
+  2. Some students may not have a foundation in machine learning, but not need to be nervous.
+     If you just want to know how to use large models, it's still easy.
+  3. follow the step, and you will have a basic understanding of the use of large models.<br>
+       "Tool": ||-python-||-pytorch-||-cuda-||-anaconda(miniconda)-||-pycharm(vscode)-||. I think it is easy for you, and there are many course on bilibili.<br>
+       "usage":<br>
+           >>first  --- download "Transformer library","Tokenizer","Pretrained Model",and you can use Tsinghua-source(清华源) and hf-mirror to download them. <br>
+           >>second --- |"import"| -> |"Tokennizer"| -> |load "Pretrained-model"| -> |input your sentence or image| -> |"model.generate"|<br>
+           >>>>example: <br>
+               >>>>||----from transformers import GPT2Tokenizer, GPT2Model--||<br>
+               >>>>||----tokenizer = GPT2Tokenizer.from_pretrained('gpt2')------||<br>
+               >>>>||----model = GPT2Model.from_pretrained('gpt2')--------------||<br>
+               >>>>||----text = "Replace me by any text you'd like."------------------||<br>
+               >>>>||----encoded_input = tokenizer(text, return_tensors='pt')---||<br>
+               >>>>||----output = model.generate(encoded_input)------------------||<br>
+        "customized": It's not a easy job. But I can give a tips that you can start with Lora. Lora as PEFT is friendly for students. And there are other ways to fine-tune the model like prefix-tuning,P-tuning,RLHF,etc. Also you can try Data mounting.
+}
+Nothing is difficult to the man who will try!