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Model: Flexan/QuantaSparkLabs-Quantum-X-GGUF-i2
Source: Original Platform

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README.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+- en
+tags:
+- qwen2.5
+- 0.5B
+- conversational
+- fast
+- lightweight
+- quantsaparklabs
+pipeline_tag: text-generation
+base_model: QuantaSparkLabs/Quantum-X
+---
+
+# GGUF Files for Quantum-X
+
+These are the GGUF files for [QuantaSparkLabs/Quantum-X](https://huggingface.co/QuantaSparkLabs/Quantum-X).
+
+> [!NOTE]  
+> **Note:** This is the **second iteration/revision** of this model. A revision is made when a model repo gets updated with a new model.
+> This is the latest version of the model.
+> 
+> [[first iteration (1)](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF-i1)]
+
+## Downloads
+
+| GGUF Link | Quantization | Description |
+| ---- | ----- | ----------- |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q2_K.gguf) | Q2_K | Lowest quality |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q3_K_S.gguf) | Q3_K_S |  |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.IQ3_S.gguf) | IQ3_S | Integer quant, preferable over Q3_K_S |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.IQ3_M.gguf) | IQ3_M | Integer quant |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q3_K_M.gguf) | Q3_K_M |  |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q3_K_L.gguf) | Q3_K_L |  |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.IQ4_XS.gguf) | IQ4_XS | Integer quant |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q4_K_S.gguf) | Q4_K_S | Fast with good performance |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q4_K_M.gguf) | Q4_K_M | **Recommended:** Perfect mix of speed and performance |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q5_K_S.gguf) | Q5_K_S |  |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q5_K_M.gguf) | Q5_K_M |  |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q6_K.gguf) | Q6_K | Very good quality |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.Q8_0.gguf) | Q8_0 | Best quality |
+| [Download](https://huggingface.co/Flexan/QuantaSparkLabs-Quantum-X-GGUF/resolve/main/Quantum-X.f16.gguf) | f16 | Full precision, don't bother; use a quant |
+
+## Note from Flexan
+
+I provide GGUFs and quantizations of publicly available models that do not have a GGUF equivalent available yet,
+usually for models **I deem interesting and wish to try out**.
+
+If there are some quants missing that you'd like me to add, you may request one in the community tab.
+If you want to request a public model to be converted, you can also request that in the community tab.
+If you have questions regarding this model, please refer to [the original model repo](https://huggingface.co/QuantaSparkLabs/Quantum-X).
+
+You can find more info about me and what I do [here](https://huggingface.co/Flexan/Flexan).
+
+# Model Card for Quantum-X
+
+<p align="center">
+  <img src="https://huggingface.co/QuantaSparkLabs/NYXIS-Pro/resolve/main/preview imgagee.png"
+       alt="NYXIS Logo"
+       width="160"
+       height="160"
+       style="border-radius: 50%; object-fit: cover;">
+</p>
+
+<p align="center">
+  <img src="https://huggingface.co/QuantaSparkLabs/NYXIS-Pro/resolve/main/logoname.png"
+       alt="NYXIS Name"
+       width="700"
+       style="border-radius: 18px;">
+</p>
+
+<p align="center">
+  <a href="https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct"><img src="https://img.shields.io/badge/Base-Qwen%202.5%200.5B-blueviolet" alt="Base Model"></a>
+  <a href="https://huggingface.co/datasets/teknium/OpenHermes-2.5"><img src="https://img.shields.io/badge/Data-OpenHermes%202.5-00BFFF" alt="Training Data"></a>
+  <a href="#"><img src="https://img.shields.io/badge/Fine--Tune-QLoRA%20%2B%20Unsloth-FF6F00" alt="Fine-Tune Method"></a>
+  <a href="#"><img src="https://img.shields.io/badge/Size-0.5B%20Params-lightgrey" alt="Model Size"></a>
+  <a href="#"><img src="https://img.shields.io/badge/Speed-Blazing%20Fast-brightgreen" alt="Speed"></a>
+  <a href="https://www.apache.org/licenses/LICENSE-2.0"><img src="https://img.shields.io/badge/License-Apache%202.0-yellow" alt="License"></a>
+</p>
+
+# Quantum-X
+
+A compact, high‑speed conversational AI built on **Qwen 2.5 0.5B** — small enough for edge devices, smart enough for real conversation.
+
+## 📋 Overview
+
+Quantum‑X is a **0.5 billion parameter** language model developed by QuantaSparkLabs. It's fine‑tuned from Qwen 2.5 0.5B on a mix of OpenHermes‑2.5 conversations and custom identity data, giving it warm, direct conversational abilities while keeping inference blazingly fast.
+
+| Feature | Detail |
+|---------|--------|
+| **Base Model** | Qwen 2.5 0.5B‑Instruct |
+| **Parameters** | ~0.5B |
+| **Fine‑tuning** | QLoRA (Unsloth), 2 epochs |
+| **Training Data** | OpenHermes‑2.5 + identity examples |
+| **Tensor Precision** | FP16 |
+| **Chat Template** | ✅ Native Qwen2 chat template |
+
+## ✨ What It Does Well
+
+- **Conversational AI**: Natural, warm dialogue with identity baked in.
+- **Factual Q&A**: Answers general knowledge questions correctly.
+- **Fast Inference**: 0.5B parameters = near‑instant responses on CPU or GPU.
+- **Edge Friendly**: Runs comfortably on 2 GB RAM, even on a phone.
+
+## 💻 Quick Start
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "QuantaSparkLabs/Quantum-X"
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+messages = [
+    {"role": "system", "content": "You are Quantum-X, created by QuantaSparkLabs."},
+    {"role": "user", "content": "What is the capital of France?"}
+]
+inputs = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+input_ids = tokenizer(inputs, return_tensors="pt").to(model.device)
+
+outputs = model.generate(**input_ids, max_new_tokens=100, temperature=0.7, do_sample=True)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## 🚀 Hardware Requirements
+
+| Environment | RAM | Storage | Ideal For |
+| :--- | :--- | :--- | :--- |
+| **CPU** | 2 GB | ~500 MB | Testing, embedded apps |
+| **GPU** | 1‑2 GB VRAM | ~500 MB | Development, serving |
+| **Edge / Mobile** | >1 GB | ~500 MB | On‑device inference |
+
+## ⚠️ Limitations
+
+- **Complex reasoning**: Multi‑step logic or advanced math may be inconsistent.
+- **Factual precision**: Can occasionally produce outdated or incorrect information.
+- **Not for high‑stakes use**: Don't use for medical, legal, or safety‑critical decisions.
+
+## 📄 License
+
+Apache 2.0
+
+---
+
+<center>Built with ❤️ by QuantaSparkLabs<br>Model ID: Quantum‑X • Rebuilt 2026</center>