Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-base_model: Daemontatox/PathFinderAI2.0
+base_model: Daemontatox/PathFinderAI3.0
 tags:
 - text-generation-inference
 - transformers
@@ -11,12 +11,49 @@ language:
 - en
 ---
 
-# Uploaded  model
+# PathFinderAI 3.0
 
-- **Developed by:** Daemontatox
-- **License:** apache-2.0
-- **Finetuned from model :** Daemontatox/PathFinderAI2.0
+PathFinderAI 3.0 is a high-performance language model designed for advanced reasoning, real-time text analysis, and decision support. Fine-tuned for diverse applications, it builds upon the capabilities of Qwen2, optimized with cutting-edge tools for efficiency and performance.
 
-This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## Features
+- **Advanced Reasoning:** Fine-tuned for real-time problem-solving and logic-driven tasks.
+- **Enhanced Performance:** Trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and the Hugging Face TRL library.
+- **Multi-domain Capability:** Excels in education, research, business, legal, and healthcare applications.
+- **Optimized Architecture:** Leverages Qwen2 for robust language understanding and generation.
+
+## Training Details
+- **Base Model:** Daemontatox/PathFinderAI3.0
+- **Training Frameworks:** [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face’s TRL library.
+- **Optimization:** Quantization-aware training for faster inference and deployment on resource-constrained environments.
+
+## Deployment
+This model is ideal for deployment on both cloud platforms and edge devices, including Raspberry Pi, utilizing efficient quantization techniques.
 
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+
+## License
+The model is open-sourced under the Apache 2.0 license.
+
+## Usage
+To load the model:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "Daemontatox/PathFinderAI3.0"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Example usage
+input_text = "What is the capital of France?"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0]))
+```
+Model Applications
+PathFinderAI 3.0 is designed for:
+
+Real-time reasoning and problem-solving
+Text generation and comprehension
+Legal and policy analysis
+Educational tutoring
+Healthcare decision support