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README.md

@@ -32,40 +32,42 @@ dtype: float16
 
 ## Model Details
 
-The merged model combines the conversational question answering capabilities of Llama3-ChatQA-1.5 with the bilingual proficiency of Llama3-8B-Chinese-Chat. Llama3-ChatQA-1.5 is designed for conversational QA and retrieval-augmented generation, leveraging a rich dataset to enhance its performance in understanding and generating contextually relevant responses. On the other hand, Llama3-8B-Chinese-Chat is fine-tuned specifically for Chinese and English users, excelling in tasks such as roleplaying and tool usage.
+The merged model combines the conversational question answering capabilities of Llama3-ChatQA-1.5-8B with the bilingual proficiency of Llama3-8B-Chinese-Chat. The former excels in retrieval-augmented generation (RAG) and conversational QA, while the latter is fine-tuned for Chinese and English interactions, enhancing its performance in multilingual contexts.
 
 ## Description
 
-This model aims to provide a seamless experience for users who require both English and Chinese language support in conversational contexts. By merging these two models, we enhance the ability to handle diverse queries, allowing for more nuanced and context-aware interactions. The model is particularly effective in scenarios where users switch between languages or require responses that incorporate cultural nuances from both English and Chinese contexts.
+This model is designed to provide a seamless experience for users seeking answers in both English and Chinese. By merging the strengths of both parent models, it aims to deliver high-quality responses across a variety of topics, making it suitable for diverse applications, including customer support, educational tools, and interactive chatbots.
 
 ## Merge Hypothesis
 
-The hypothesis behind this merge is that combining the strengths of both models will yield a more capable and flexible conversational agent. The Llama3-ChatQA-1.5 model's proficiency in QA tasks complements the Llama3-8B-Chinese-Chat's bilingual capabilities, resulting in a model that can effectively engage users in both languages.
+The hypothesis behind this merge is that combining the advanced conversational capabilities of Llama3-ChatQA-1.5 with the bilingual strengths of Llama3-8B-Chinese-Chat will yield a model that not only understands context better but also responds more accurately in both languages. This is particularly beneficial for users who require multilingual support in their interactions.
 
 ## Use Cases
 
-- **Bilingual Customer Support**: Providing assistance in both English and Chinese for customer inquiries.
-- **Language Learning**: Assisting learners in practicing conversational skills in both languages.
-- **Cultural Exchange**: Facilitating discussions that require understanding of cultural references in both English and Chinese.
+- **Customer Support**: Providing assistance in both English and Chinese, catering to a wider audience.
+- **Educational Tools**: Assisting learners in understanding concepts in their preferred language.
+- **Interactive Chatbots**: Engaging users in natural conversations, regardless of their language preference.
 
 ## Model Features
 
 - **Bilingual Proficiency**: Capable of understanding and generating text in both English and Chinese.
-- **Conversational QA**: Enhanced ability to answer questions based on context, leveraging retrieval-augmented generation techniques.
-- **Roleplaying and Tool Usage**: Supports interactive scenarios where users can engage in roleplay or request tool-based assistance.
+- **Enhanced Context Understanding**: Improved ability to maintain context over longer conversations.
+- **Conversational QA**: Designed to answer questions accurately and contextually.
 
 ## Evaluation Results
 
-The performance of the parent models in various benchmarks indicates strong capabilities in their respective domains. For instance, Llama3-ChatQA-1.5 has shown impressive results in conversational QA tasks, while Llama3-8B-Chinese-Chat has excelled in bilingual interactions, surpassing previous models in specific benchmarks.
+The evaluation results of the parent models indicate strong performance in their respective tasks. For instance, Llama3-ChatQA-1.5-8B has shown impressive results in various benchmarks, such as:
 
-| Benchmark | Llama3-ChatQA-1.5-8B | Llama3-8B-Chinese-Chat |
-|-----------|------------------------|-------------------------|
-| Doc2Dial  | 41.26                  | N/A                     |
-| QuAC      | 38.82                  | N/A                     |
-| Average    | 58.25                  | N/A                     |
+| Benchmark | ChatQA-1.5-8B |
+|-----------|----------------|
+| Doc2Dial  | 41.26          |
+| QuAC      | 38.82          |
+| CoQA      | 78.44          |
+
+Llama3-8B-Chinese-Chat has also demonstrated superior performance in Chinese language tasks, surpassing previous models in various evaluations.
 
 ## Limitations of Merged Model
 
-While the merged model offers enhanced capabilities, it may still inherit some limitations from the parent models. Potential biases in language understanding, particularly in cultural contexts, may affect the quality of responses. Additionally, the model's performance may vary based on the complexity of the queries and the context provided.
+While the merged model benefits from the strengths of both parent models, it may also inherit some limitations. For instance, biases present in the training data of either model could affect the responses. Additionally, the model may struggle with highly specialized topics or nuanced cultural references that are less represented in the training data.
 
-In summary, Llama3-ChatQA-1.5-Llama3-8B-Chinese-Chat-linear-merge represents a significant step towards creating a more inclusive and capable conversational AI, bridging the gap between English and Chinese interactions.
+In summary, Llama3-ChatQA-1.5-8B-Llama3-8B-Chinese-Chat-linear-merge represents a significant step forward in creating a bilingual conversational AI, but users should remain aware of its limitations and potential biases.