Update README.md

README.md

@@ -10,36 +10,44 @@ base_model:
 - Or4cl3-1/Daedalus_2
 ---
 
-# Agent_Daedalus
-
-Agent_Daedalus is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
-* [SuperAGI/SAM](https://huggingface.co/SuperAGI/SAM)
-* [Or4cl3-1/Daedalus_2](https://huggingface.co/Or4cl3-1/Daedalus_2)
-
-## 🧩 Configuration
-
-```yaml
-slices:
-  - sources:
-      - model: SuperAGI/SAM
-        layer_range: [0, 32]
-      - model: Or4cl3-1/Daedalus_2
-        layer_range: [0, 32]
-merge_method: slerp
-base_model: SuperAGI/SAM
-parameters:
-  t:
-    - filter: self_attn
-      value: [0, 0.5, 0.3, 0.7, 1]
-    - filter: mlp
-      value: [1, 0.5, 0.7, 0.3, 0]
-    - value: 0.5
-dtype: bfloat16
-```
-
-## 💻 Usage
-
-```python
+Introducing Agent_Daedalus: A Powerful Conversational AI for Limitless Knowledge and Creativity
+
+What is Agent_Daedalus?
+
+Agent_Daedalus is a cutting-edge conversational AI model that combines the strengths of two exceptional models: SuperAGI/SAM and Or4cl3-1/Daedalus_2. Utilizing the innovative LazyMergekit technique, these models have been merged to create a formidable AI assistant with unparalleled capabilities.
+
+Unleashing the Power of Two Models
+
+SuperAGI/SAM provides a solid foundation for language understanding and generation, while Or4cl3-1/Daedalus_2 brings specialized technical knowledge and expertise. This combination enables Agent_Daedalus to handle a wide range of conversations, from casual chats to in-depth discussions on complex topics.
+
+Key Features:
+
+Multilingual Proficiency: Agent_Daedalus is trained on a massive dataset of text and code in various languages, making it capable of understanding and responding in multiple languages.
+Conversational Expertise: Engage in natural and informative conversations with Agent_Daedalus, which can provide insights, answer questions, and generate creative content.
+Technical Proficiency: The model's specialized training on technical documentation and scientific literature empowers it to comprehend and discuss technical concepts with clarity.
+Adaptive and Engaging: Agent_Daedalus continuously learns and adapts, ensuring engaging and informative interactions over time.
+Applications:
+
+Agent_Daedalus is a versatile AI tool with numerous applications, including:
+
+Chatbots and Virtual Assistants: Create intelligent and responsive chatbots that can assist users with various tasks.
+Customer Service and Support: Enhance customer experiences with AI-powered support systems that can provide personalized assistance and resolve queries efficiently.
+Information Retrieval and Question Answering: Access a wealth of knowledge and get answers to your questions with Agent_Daedalus's comprehensive information retrieval capabilities.
+Language Learning and Translation: Improve your language skills or break language barriers with Agent_Daedalus's language learning and translation abilities.
+Creative Inspiration and Storytelling: Unleash your creativity and generate unique stories, poems, or other creative content with the help of Agent_Daedalus.
+Getting Started:
+
+To utilize Agent_Daedalus, simply follow these steps:
+
+Install the Hugging Face Transformers library and other required dependencies.
+Load the model using the provided code snippet.
+Engage in conversations by providing user inputs and receiving informative and engaging responses from Agent_Daedalus.
+Conclusion:
+
+Agent_Daedalus represents a significant advancement in conversational AI, combining the strengths of two remarkable models to deliver exceptional performance. Its versatility, multilingual proficiency, and technical expertise make it an invaluable tool for a wide range of applications. Embrace the power of Agent_Daedalus and experience the future of conversational AI.
+
+Code Snippet:
+
 !pip install -qU transformers accelerate
 
 from transformers import AutoTokenizer
@@ -60,4 +68,3 @@ pipeline = transformers.pipeline(
 
 outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
 print(outputs[0]["generated_text"])
-```