Update README.md

README.md

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 This model was converted to GGUF format from [`Spestly/Athena-1-14B`](https://huggingface.co/Spestly/Athena-1-14B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/Spestly/Athena-1-14B) for more details on the model.
 
+---
+Model details:
+-
+Athena 1 is a state-of-the-art language model fine-tuned from Qwen/Qwen2.5-14B-Instruct.
+ Designed to excel in instruction-following tasks, Athena 1 delivers 
+advanced capabilities in text generation, coding, mathematics, and 
+long-context understanding. It is optimized for a wide variety of use 
+cases, including conversational AI, structured data interpretation, and 
+multilingual applications. It outperforms Ava 1.5 in many aspects making
+ Athena-1 the superior model.
+
+
+
+
+	
+		
+	
+
+		Key Features
+	
+
+
+
+
+	
+		
+	
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+		🚀 Enhanced Capabilities
+	
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+
+
+Instruction Following: Athena 1 has been fine-tuned
+ for superior adherence to user prompts, making it ideal for chatbots, 
+virtual assistants, and guided workflows.
+Coding and Mathematics: Specialized fine-tuning enhances coding problem-solving and mathematical reasoning.
+Long-Context Understanding: Handles input contexts up to 128K tokens and generates up to 8K tokens.
+
+
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+	
+		
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+		🌐 Multilingual Support
+	
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+
+Supports 29+ languages, including:
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+
+English, Chinese, French, Spanish, Portuguese, German, Italian, Russian
+Japanese, Korean, Vietnamese, Thai, Arabic, and more.
+
+
+
+	
+		
+	
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+		📊 Structured Data & Outputs
+	
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+
+Structured Data Interpretation: Understands and processes structured formats like tables and JSON.
+Structured Output Generation: Generates well-formatted outputs, including JSON, XML, and other structured formats.
+
+
+
+
+	
+		
+	
+
+		Model Details
+	
+
+
+
+Base Model: Qwen/Qwen2.5-14B-Instruct
+Architecture: Transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias.
+Parameters: 14.7B total (13.1B non-embedding).
+Layers: 48
+Attention Heads: 40 for Q, 8 for KV.
+Context Length: Up to 131,072 tokens.
+
+
+
+
+	
+		
+	
+
+		Applications
+	
+
+
+
+Athena 1 is designed for a wide range of use cases:
+
+
+Conversational AI and chatbots.
+Code generation, debugging, and explanation.
+Mathematical problem-solving.
+Large-document summarization and analysis.
+Multilingual text generation and translation.
+Structured data processing (e.g., tables, JSON).
+
+
+
+
+	
+		
+	
+
+		Quickstart
+	
+
+
+
+Below is an example of how to use Athena 1 for text generation:
+
+
+huggingface-cli login
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe = pipeline("text-generation", model="Spestly/Athena-1-14B")
+pipe(messages)  
+
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("Spestly/Athena-1-14B")
+model = AutoModelForCausalLM.from_pretrained("Spestly/Athena-1-14B")
+
+
+
+
+	
+		
+	
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+		Performance
+	
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+Athena 1 has been optimized for efficiency and performance on modern 
+GPUs. For detailed evaluation metrics (e.g., throughput, accuracy, and 
+memory requirements), refer to the Qwen2.5 performance benchmarks.
+
+
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+	
+		
+	
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+		Requirements
+	
+
+
+
+To use Athena 1, ensure the following:
+
+
+Python >= 3.8
+Transformers >= 4.37.0 (to support Qwen models)
+PyTorch >= 2.0
+GPU with BF16 support for optimal performance.
+
+
+
+	
+		
+	
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+		Citation
+	
+
+
+
+If you use Athena 1 in your research or projects, please cite its base model Qwen2.5 as follows:
+
+
+@misc{qwen2.5,
+    title = {Qwen2.5: A Party of Foundation Models},
+    url = {https://qwenlm.github.io/blog/qwen2.5/},
+    author = {Qwen Team},
+    month = {September},
+    year = {2024}
+}
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)