Spestly
/

Athena-3-7B

@@ -4,13 +4,13 @@ base_model:
 - rubenroy/Zurich-7B-GCv2-5m
 library_name: transformers
 ---
-# Maverick Model Card
-## Model Overview
 **Maverick** is a 14.7-billion-parameter causal language model fine-tuned from [Ruben Roy's Zurich-14B-GCv2-5m](https://huggingface.co/rubenroy/Zurich-14B-GCv2-5m). The base model, Zurich-14B-GCv2-5m, is itself a fine-tuned version of Alibaba's Qwen 2.5 14B Instruct model, trained on the GammaCorpus v2-5m dataset. Maverick is designed to excel in various STEM fields and general natural language processing tasks, offering enhanced reasoning and instruction-following capabilities.
-## Model Details
 - **Model Developer:** Aayan Mishra
 - **Model Type:** Causal Language Model
@@ -23,11 +23,11 @@ library_name: transformers
 - **Languages Supported:** Over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic
 - **License:** MIT
-## Training Details
 Maverick was fine-tuned using the Unsloth framework on a single NVIDIA A100 GPU. The fine-tuning process spanned approximately 90 minutes over 60 epochs, utilising a curated dataset focused on instruction-following and STEM-related content. This approach aimed to enhance the model's performance in complex reasoning and academic tasks.
-## Intended Use
 Maverick is designed for a range of applications, including but not limited to:
@@ -38,9 +38,9 @@ Maverick is designed for a range of applications, including but not limited to:
 While Maverick is a powerful tool for various applications, it is not intended for real-time, safety-critical systems or for processing sensitive personal information.
-## How to Use
-To utilize Maverick, ensure that you have the latest version of the `transformers` library installed:
 ```bash
 pip install transformers
@@ -85,7 +85,7 @@ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
 print(response)
 ```
-## Limitations
 Users should be aware of the following limitations:
@@ -93,10 +93,14 @@ Users should be aware of the following limitations:
 - **Knowledge Cutoff:** The model's knowledge is current up to August 2024. It may not be aware of events or developments occurring after this date.
 - **Language Support:** While primarily trained on English data, performance in other languages may be inconsistent.
-## Acknowledgements
 Maverick builds upon the work of [Ruben Roy](https://huggingface.co/rubenroy), particularly the Zurich-14B-GCv2-5m model, which is a fine-tuned version of Alibaba's Qwen 2.5 14B Instruct model. Gratitude is also extended to the open-source AI community for their contributions to tools and frameworks that facilitated the development of Maverick.
-## License
-Maverick is released under the [MIT License](https://opensource.org/license/mit), permitting wide usage with proper attribution.

 - rubenroy/Zurich-7B-GCv2-5m
 library_name: transformers
 ---
+# **Maverick Model Card**
+## **Model Overview**
 **Maverick** is a 14.7-billion-parameter causal language model fine-tuned from [Ruben Roy's Zurich-14B-GCv2-5m](https://huggingface.co/rubenroy/Zurich-14B-GCv2-5m). The base model, Zurich-14B-GCv2-5m, is itself a fine-tuned version of Alibaba's Qwen 2.5 14B Instruct model, trained on the GammaCorpus v2-5m dataset. Maverick is designed to excel in various STEM fields and general natural language processing tasks, offering enhanced reasoning and instruction-following capabilities.
+## **Model Details**
 - **Model Developer:** Aayan Mishra
 - **Model Type:** Causal Language Model
 - **Languages Supported:** Over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic
 - **License:** MIT
+## **Training Details**
 Maverick was fine-tuned using the Unsloth framework on a single NVIDIA A100 GPU. The fine-tuning process spanned approximately 90 minutes over 60 epochs, utilising a curated dataset focused on instruction-following and STEM-related content. This approach aimed to enhance the model's performance in complex reasoning and academic tasks.
+## **Intended Use**
 Maverick is designed for a range of applications, including but not limited to:
 While Maverick is a powerful tool for various applications, it is not intended for real-time, safety-critical systems or for processing sensitive personal information.
+## **How to Use**
+To utilise Maverick, ensure that you have the latest version of the `transformers` library installed:
 ```bash
 pip install transformers
 print(response)
 ```
+## **Limitations**
 Users should be aware of the following limitations:
 - **Knowledge Cutoff:** The model's knowledge is current up to August 2024. It may not be aware of events or developments occurring after this date.
 - **Language Support:** While primarily trained on English data, performance in other languages may be inconsistent.
+## **Acknowledgements**
 Maverick builds upon the work of [Ruben Roy](https://huggingface.co/rubenroy), particularly the Zurich-14B-GCv2-5m model, which is a fine-tuned version of Alibaba's Qwen 2.5 14B Instruct model. Gratitude is also extended to the open-source AI community for their contributions to tools and frameworks that facilitated the development of Maverick.
+## **License**
+Maverick is released under the [MIT License](https://opensource.org/license/mit), permitting wide usage with proper attribution.
+## **Contact**
+- Email: [email protected]