Update README.md

README.md

@@ -12,58 +12,44 @@ pipeline_tag: text2text-generation
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+**This is a Chinese-English translation model based on Transformer architecture(beta version 0.0.1).**
+This modelcard aims to be a base template for new models. 
 
 ## Model Details
 
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
-This model aims to provide the service of traslation between Chinese and English(Only Chinese to English available now), which based on wmt19dataset.
+This model aims to provide the service of traslation between Chinese and English(Only Chinese to English available now), which based on wmt19 dataset.  
+
 The model is good at grammar in translation betweeen zh-en, if you don't want to fork this repository, just try the API reference aside this page ^_^
 
 
-- **Developed by:** Varine
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Developed by:** **Varine**
+- **Shared by:** **TianQi Xu**
+- **Model type:** **Tranformer**
+- **Language(s) (NLP):** **Chinese, English**
+- **License:** **MIT**
+- **Finetuned from model:** **opus-mt-zh-en-fintuned-zhen-checkpoints**
 
-### Model Sources [optional]
+### Model Sources
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** <https://huggingface.co/Varine/opus-mt-zh-en-model>
 
 ## Uses
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
+This model can be used in tranlation missions between Chinese and English.
 ### Direct Use
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+As it's a traditional translation model, it can be used in many circumstances, including translation between some academical papers, news, and **even some of the literary works(as the excellent performance the model is in grammar and multi-context cases)**.  
 
 ## Bias, Risks, and Limitations
-
+**1.Remember this is a beta version of this translation model,thus we add the limitation on the scale of input tokens, so plz make sure the scale of your input text won't overflow the limit.**
+**2.DO NOT APPLY THIS MODEL FOR ILLEGAL USES.**
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
 [More Information Needed]
@@ -76,21 +62,31 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
+Before we enjoy this model, Plz follow the possible directions to make sure your environment is appropriate.Use the code below to get started with the model.  
 
-[More Information Needed]
+1.Use git tools to fork this repository(If you don't wan't to torture youself in configuring environment, just feel free to use API!):  
+```
+git clone "https://huggingface.co/Varine/opus-mt-zh-en-model"
+```
+2.After forking, plz make sure you have installed the modules below in your Jupiter Notebook or other IDEs:  
+```
+! pip install transformers datasets numpy
+```
+3.After checking the packages, plz run the code in [translation.ipynb](https://huggingface.co/Varine/opus-mt-zh-en-model/translation.ipynb), and a Jupiter Notebook environment is recommended in this step.  
+4.Ultimately you can enjoy the whole model my loading the model by code and pipelining translation strategy, and don't forget to input your text!
 
 ## Training Details
 
 ### Training Data
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
+- wmt/wmt19
 
 ### Training Procedure
 
 <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+As the dataset we choose in training is tremendous in scale, so after analyzing, we decided to use the only 4% among the whole dataset to train, and we divided the 4% data in 10 epoch to evaluate the training loss and and validation loss in every part of the epoch.  
+Moreover, we need to claim that, the data form that we used in our training progress is Chinese-English sentence pairs(to better embedding and compare them in higher-dimension space in Transformer architecture).  
 
 #### Preprocessing [optional]