Update README.md

README.md

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----
-license: apache-2.0
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+---
+license: apache-2.0
+---
+
+---
+tags:
+- autotrain
+- text-generation-inference
+- text-generation
+- peft
+library_name: transformers
+base_model: meta-llama/Meta-Llama-3.1-8B
+widget:
+  - messages:
+      - role: user
+        content: What challenges do you enjoy solving?
+license: apache-2.0
+---
+
+**SpectraMind Quantum LLM** **GGUF-Compatible and Fully Optimized**
+
+![SpectraMind](https://huggingface.co/shafire/SpectraMind/resolve/main/spectramind.png)
+
+SpectraMind is an advanced, multi-layered language model built with quantum-inspired data processing techniques. Trained on custom datasets with unique quantum reasoning enhancements, SpectraMind integrates ethical decision-making frameworks with deep problem-solving capabilities, handling complex, multi-dimensional tasks with precision.
+
+![SpectraMind Performance](https://huggingface.co/shafire/SpectraMind/resolve/main/performance_chart.png)
+
+<a href="https://www.youtube.com/watch?v=xyz123">Watch Our Model in Action</a>
+
+**Use Cases**:
+This model is ideal for advanced NLP tasks, including ethical decision-making, multi-variable reasoning, and comprehensive problem-solving in quantum and mathematical contexts.
+
+**Key Highlights of SpectraMind:**
+
+- **Quantum-Enhanced Reasoning**: Designed for tackling complex ethical questions and multi-layered logic problems, SpectraMind applies quantum-math techniques in AI for nuanced solutions.
+- **Refined Dataset Curation**: Data was refined over multiple iterations, focusing on clarity and consistency, to align with SpectraMind's quantum-based reasoning. 
+- **Iterative Training**: The model underwent extensive testing phases to ensure accurate and reliable responses.
+- **Optimized for CPU Inference**: Compatible with web UIs and desktop interfaces like `oobabooga` and `lm studio`, and performs well in self-hosted environments for CPU-only setups.
+
+**Model Overview**
+
+- **Developer**: Shafaet Brady Hussain - [ResearchForum](https://researchforum.online)
+- **Funded by**: [Researchforum.online](https://researchforum.online)
+- **Language**: English
+- **Model Type**: Causal Language Model
+- **Base Model**: LLaMA 3.1 8B (Meta)
+- **License**: Apache-2.0
+
+**Usage**: Run on any web interface or as a bot for self-hosted solutions. Designed to run smoothly on CPU.
+
+**Tested on CPU - Ideal for Local and Self-Hosted Environments**
+
+AGENT INTERFACE DETAILS:
+![SpectraMind Agent Interface](https://huggingface.co/shafire/SpectraMind/resolve/main/interface_screenshot.png)
+
+---
+
+### Usage Code Example:
+
+You can load and interact with SpectraMind using the following code snippet:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = "PATH_TO_THIS_REPO"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(
+    model_path,
+    device_map="auto",
+    torch_dtype="auto"
+).eval()
+
+# Example prompt
+messages = [
+    {"role": "user", "content": "What challenges do you enjoy solving?"}
+]
+
+input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
+output_ids = model.generate(input_ids.to("cuda"))
+response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
+
+print(response)  # Prints the model's response