Update README.md

README.md

@@ -1,5 +1,6 @@
 ---
-base_model: unsloth/qwen2.5-14b-instruct-bnb-4bit
+base_model:
+- Qwen/Qwen2.5-14B-Instruct
 tags:
 - text-generation-inference
 - transformers
@@ -10,100 +11,4 @@ license: apache-2.0
 language:
 - en
 ---
-![Header](https://raw.githubusercontent.com/Aayan-Mishra/Images/refs/heads/main/Athena.png)
 
-# Athena 1:
-
-Athena 1 is a state-of-the-art language model fine-tuned from [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/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
-
-### 🚀 Enhanced Capabilities
-- **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.
-
-### 🌐 Multilingual Support
-Supports 29+ languages, including:
-- English, Chinese, French, Spanish, Portuguese, German, Italian, Russian
-- Japanese, Korean, Vietnamese, Thai, Arabic, and more.
-
-### 📊 Structured Data & Outputs
-- **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](https://huggingface.co/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:
-
-```python
-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")
-```
-
-## Performance
-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.
-
----
-
-## 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.
-
-## 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}
-}
-```