Update README.md

README.md

@@ -32,13 +32,11 @@ We construct a comprehensive instruction dataset for detoxification of LLMs, and
 
 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]
+- **Developed by:** Sungjoo Byun (Grace Byun)
 - **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Language(s) (NLP):** English
+- **License:** Apache license 2.0
+- **Finetuned from model [optional]:** meta-llama/Llama-2-7b-hf
 
 ### Model Sources [optional]
 
@@ -52,40 +50,24 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-tokenizer = AutoTokenizer.from_pretrained("SungJoo/llama2-7b-sft-detox")
-model = AutoModelForCausalLM.from_pretrained("SungJoo/llama2-7b-sft-detox")
-
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
 [More Information Needed]
 
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
 
 ## How to Get Started with the Model
 
 Use the code below to get started with the model.
 
-[More Information Needed]
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("SungJoo/llama2-7b-sft-detox")
+model = AutoModelForCausalLM.from_pretrained("SungJoo/llama2-7b-sft-detox")
+```
 
 ## Training Details