Update README.md

README.md

@@ -74,4 +74,26 @@ model = AutoModelForCausalLM.from_pretrained(model_name)
 prompt = "Explain the Pythagorean theorem step-by-step:"
 inputs = tokenizer(prompt, return_tensors="pt")
 outputs = model.generate(**inputs)
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Optimized Inference:
+Install the transformers and text-generation-inference libraries.
+Deploy on servers or edge devices using quantized models for optimal performance.
+Training Data
+The fine-tuning process utilized reasoning-specific datasets, including:
+
+### MATH Dataset: Focused on logical and mathematical problems.
+### Custom Corpora: Tailored datasets for multi-domain reasoning and structured problem-solving.
+### Ethical Considerations
+### Bias Awareness: The model reflects biases present in the training data. Users should carefully evaluate outputs in sensitive contexts.
+### Safe Deployment: Not recommended for generating harmful or unethical content.
+
+## Acknowledgments
+This model was developed with contributions from Daemontatox and the Unsloth team, utilizing state-of-the-art techniques in fine-tuning and optimization.
+
+For more information or collaboration inquiries, please contact:
+
+Author: Daemontatox
+GitHub: Daemontatox GitHub Profile
+Unsloth: Unsloth GitHub