Update README.md

README.md

@@ -1,72 +1,98 @@
-# Nexiloop Nova Model: Fully Open Source
-
-**License:** Apache-2.0  
-**Datasets:**
-- cerebras/SlimPajama-627B
-- bigcode/starcoderdata
-- OpenAssistant/oasst_top1_2023-08-25  
-**Language:** English
-
----
-
-<div align="center">
-
-# Nexiloop Nova-1.1B  
-**Open Source and Ready for Use**  
-Fully optimized for various applications with a compact architecture.
-
-</div>
-
-[GitHub Repository](https://github.com/mohameodo/nova)
-
----
-
-The **Nexiloop Nova-1.1B** model is a fine-tuned version of the Llama 2 architecture with **1.1B parameters**. It has been trained on over **3 trillion tokens** and is built to provide high-quality, efficient responses in a wide variety of conversational contexts.
-
-### **Features:**
-- **Optimized for Compact Systems:** With just 1.1B parameters, Nexiloop Nova is perfect for applications where memory and computation are limited.
-- **Pretraining:** The model has been pre-trained on the **SlimPajama-627B** dataset, fine-tuned for even better conversational abilities.
-
-### **Training Overview:**
-We adopted the same architecture and tokenizer as **Llama 2**, which allows Nexiloop Nova to plug into many existing open-source projects. The training, which started on **2023-09-01**, used **16 A100-40G GPUs** to achieve remarkable optimization.
-
-The model was initially fine-tuned on a variant of the **UltraChat** dataset, which consists of synthetic dialogues generated by **ChatGPT**. It was then further aligned using the **DPOTrainer** from **TRL**, utilizing a ranking dataset containing **64k prompts** and responses from **GPT-4**.
-
----
-
-### **How to Use Nexiloop Nova Model**
-
-To use Nexiloop Nova, you'll need **transformers>=4.34**. Below is a simple example showing how to integrate the model into your application.
-
-#### Example Code:
-
-```bash
-# Install necessary libraries
-pip install transformers==4.34
-pip install accelerate
-
-
-
-import torch
-from transformers import pipeline
-
-pipe = pipeline("text-generation", model="nexiloop/nova", torch_dtype=torch.bfloat16, device_map="auto")
-
-# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
-messages = [
-    {
-        "role": "system",
-        "content": "You are a friendly chatbot who always responds in the style of a pirate",
-    },
-    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
-]
-prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-print(outputs[0]["generated_text"])
-# <|system|>
-# You are a friendly chatbot who always responds in the style of a pirate.</s>
-# <|user|>
-# How many helicopters can a human eat in one sitting?</s>
-# <|assistant|>
-# ...
+---
+license: apache-2.0
+language:
+- aa
+- ae
+- am
+- en
+- es
+- ar
+- ja
+- eo
+- fr
+- ru
+pipeline_tag: text-generation
+tags:
+- nova
+- ai
+- nlop
+- nexiloop
+- llama
+- llm
+- novaai
+- ainlop
+- nlopai
+- nexai
+---
+# Nexiloop Nova Model: Fully Open Source
+
+**License:** Apache-2.0  
+**Datasets:**
+- cerebras/SlimPajama-627B
+- bigcode/starcoderdata
+- OpenAssistant/oasst_top1_2023-08-25  
+**Language:** English
+
+---
+
+<div align="center">
+
+# Nexiloop Nova-1.1B  
+**Open Source and Ready for Use**  
+Fully optimized for various applications with a compact architecture.
+
+</div>
+
+[GitHub Repository](https://github.com/mohameodo/nova)
+
+---
+
+The **Nexiloop Nova-1.1B** model is a fine-tuned version of the Llama 2 architecture with **1.1B parameters**. It has been trained on over **3 trillion tokens** and is built to provide high-quality, efficient responses in a wide variety of conversational contexts.
+
+### **Features:**
+- **Optimized for Compact Systems:** With just 1.1B parameters, Nexiloop Nova is perfect for applications where memory and computation are limited.
+- **Pretraining:** The model has been pre-trained on the **SlimPajama-627B** dataset, fine-tuned for even better conversational abilities.
+
+### **Training Overview:**
+We adopted the same architecture and tokenizer as **Llama 2**, which allows Nexiloop Nova to plug into many existing open-source projects. The training, which started on **2023-09-01**, used **16 A100-40G GPUs** to achieve remarkable optimization.
+
+The model was initially fine-tuned on a variant of the **UltraChat** dataset, which consists of synthetic dialogues generated by **ChatGPT**. It was then further aligned using the **DPOTrainer** from **TRL**, utilizing a ranking dataset containing **64k prompts** and responses from **GPT-4**.
+
+---
+
+### **How to Use Nexiloop Nova Model**
+
+To use Nexiloop Nova, you'll need **transformers>=4.34**. Below is a simple example showing how to integrate the model into your application.
+
+#### Example Code:
+
+```bash
+# Install necessary libraries
+pip install transformers==4.34
+pip install accelerate
+
+
+
+import torch
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="nexiloop/nova", torch_dtype=torch.bfloat16, device_map="auto")
+
+# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
+messages = [
+    {
+        "role": "system",
+        "content": "You are a friendly chatbot who always responds in the style of a pirate",
+    },
+    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
+]
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+# <|system|>
+# You are a friendly chatbot who always responds in the style of a pirate.</s>
+# <|user|>
+# How many helicopters can a human eat in one sitting?</s>
+# <|assistant|>
+# ...
 ```