Update README.md

README.md

@@ -5,7 +5,7 @@ metrics:
 - bleurt
 
 model-index:
-- name: ibleducation/ibl-tutoring-llm-openchat
+- name: ibleducation/ibl-tutoring-chat-7B
   results:
   - task:
       name: truthfulqa_gen
@@ -64,10 +64,11 @@ model-index:
 library_name: transformers
 ---
 
-# ibleducation/ibl-tutoring-llm-openchat
-ibleducation/ibl-tutoring-llm-openchat is a model finetuned on top of openchat/openchat_3.5
+# ibleducation/ibl-tutoring-chat-7B
+ibleducation/ibl-tutoring-chat-7B is a model finetuned on top of openchat/openchat_3.5
 
-This model is finetuned to give responses in a way befitting of a professional teacher
+This model is finetuned to give responses in a way befitting of a professional teacher. 
+It is finetuned to exhibit characteristics and virtues such as compassion, encouragement, friendliness and more.
 
 
 ## Example Conversations
@@ -84,12 +85,6 @@ This model is finetuned to give responses in a way befitting of a professional t
    ```
   
 
-## Motivation of Developing ibl-tutoring-llm-32k Model
-
-Students today use llm's in their learning and research. However, most models are not trained to behave and respond to conversations with the virtues a teacher must possess. ibl-tutoring-llm-32k Model is fine tuned 
-on top of amazon/Mistrallite to alter its behaviour to converse the way a teacher should
-
-
 ## Model Details
 
 - **Developed by:** [IBL Education](https://ibl.ai)
@@ -98,10 +93,10 @@ on top of amazon/Mistrallite to alter its behaviour to converse the way a teache
 - **Language:** English
 - **Finetuned from weights:** [OpenChat 3.5](https://huggingface.co/openchat/openchat_3.5)
 - **Finetuned on data:**
-  - IBL-tutoring-dataset (private)
+  - ibl-best-practices-instructor-dataset (private)
 - **Model License:** Apache 2.0
 
-## How to Use ibl-tutoring-llm-openchat Model from Python Code (HuggingFace transformers) ##
+## How to Use ibl-tutoring-chat-7B Model from Python Code (HuggingFace transformers) ##
 
 ### Install the necessary packages
 
@@ -119,7 +114,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 import transformers
 import torch
 
-model_id = "ibleducation/ibl-tutoring-llm-openchat"
+model_id = "ibleducation/ibl-tutoring-chat-7B"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(
@@ -144,7 +139,7 @@ sequences = pipeline(
 for seq in sequences:
     print(f"{seq['generated_text']}")
 ```
-**Important** - Use the prompt template below for ibl-tutoring-llm-32k:
+**Important** - Use the prompt template below for ibl-tutoring-chat-7B:
 ```
 <s>{prompt}</s>
 ```