Update README.md

README.md

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 ---
 library_name: transformers
-tags: []
+language:
+- en
+pipeline_tag: text-generation
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+Coder-2b is a phi-2 fine tuned model trained on jondurbin/py-dpo-v0.1 using Reinforcement Learning from Human Feedback with DPO. 
+it is an instruct model capable of generating code starting from an instruction given by the user. 
+It is intended for those people who have few hardware resources available and want to speed up the process of writing Python code.
 
 
 
@@ -13,29 +17,26 @@ tags: []
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+with the idea of creating a model that works on limited hardware, starting from a phi-2 model, coder-2b was fine-tuned with the Vezora/Tested-22k-Python-Alpaca dataset to make it capable of creating python code starting from from a user-written prompt. With further fine tuning, using the jondurbin/py-dpo-v0.1 dataset and leveraging the RLHF DPO technique, the model was further improved to produce more accurate outputs. 
 
-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]
-- **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:** Lodo97
+- **Language(s) (NLP):** English
+- **Finetuned from model Lodo97/Test1:** 
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
+- **Repository:** Lodo97/coder-2b-v0.1-hfrl
 - **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. -->
+- Generate python code from an instruction provided by the user
+- Find errors and bugs
+- Rewrite code 
 
 ### Direct Use