| --- |
| 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|> |
| # ... |
| ``` |
