commit ce8e764ce39193adcf20f8294f552df44f525ee0 Author: ModelHub XC Date: Sat Aug 29 03:14:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: Flexan/QuantaSparkLabs-Quantum-X-GGUF-i2 Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..d5087bf --- /dev/null +++ b/.gitattributes @@ -0,0 +1,49 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs 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file mode 100644 index 0000000..42070af --- /dev/null +++ b/README.md @@ -0,0 +1,153 @@ +--- +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 + +

+ NYXIS Logo +

+ +

+ NYXIS Name +

+ +

+ Base Model + Training Data + Fine-Tune Method + Model Size + Speed + License +

+ +# 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 + +--- + +
Built with ❤️ by QuantaSparkLabs
Model ID: Quantum‑X • Rebuilt 2026
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