README.md

---
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