Update README.md

README.md

@@ -1,11 +1,15 @@
 ---
 library_name: transformers
-tags: []
+license: apache-2.0
+datasets:
+- code_search_net
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+This model identifies foreign code and determines the recognized programming language.
+It is currently not further trained and has been completely adopted by huggingface/CodeBERTa-language-id.
+[source: https://huggingface.co/huggingface/CodeBERTa-language-id]
 
 
 
@@ -17,25 +21,41 @@ tags: []
 
 This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-- **Developed by:** [More Information Needed]
+- **Developed by:** Husain, Hamel and Wu, Ho-Hsiang and Gazit, Tiferet and Allamanis, Miltiadis and Brockschmidt, Marc
 - **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]
+- **License:** apache-2.0
+- **Finetuned from model [optional]:** huggingface/CodeBERTa-language-id
+- **base_model**: huggingface/CodeBERTa-small-v1
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
+- **Repository:** https://huggingface.co/huggingface/CodeBERTa-language-id/edit/main/README.md
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 
 ## 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. -->
+```python
+from transformers import pipeline
+
+checkpoint = "malteklaes/based-CodeBERTa-language-id-llm-module"
+
+from transformers import TextClassificationPipeline
+
+myPipeline = TextClassificationPipeline(
+    model=RobertaForSequenceClassification.from_pretrained(checkpoint),
+    tokenizer=RobertaTokenizer.from_pretrained(checkpoint)
+)
+
+CODE_TO_IDENTIFY = "print('hello world')"
+myPipeline(CODE_TO_IDENTIFY)
+```
 
 ### Direct Use
 
@@ -79,7 +99,7 @@ Use the code below to get started with the model.
 
 <!-- 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]
+code_search_net
 
 ### Training Procedure 
 
@@ -196,6 +216,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## Model Card Contact
 
-[More Information Needed]
-
-
+[More Information Needed]