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Model: muverqqw/Noir-Ultra Source: Original Platform
2026-06-13 10:50:16 +08:00
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+---
+base_model: unsloth/Qwen2.5-7B-Instruct # Уточни, если база другая
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen2
+- reasoning
+- science
+- logic
+- trl
+- sft
+license: apache-2.0
+language:
+- en
+- ru
+- zh
+model-index:
+- name: Noir-Ultra
+  results:
+  - task:
+      type: text-generation
+      name: STEM (Science)
+    dataset:
+      name: SciQ
+      type: sciq
+    metrics:
+    - name: accuracy
+      type: exact_match
+      value: 91.0
+  - task:
+      type: text-generation
+      name: Mathematics
+    dataset:
+      name: GSM8K
+      type: gsm8k
+    metrics:
+    - name: accuracy
+      type: exact_match
+      value: 84.0
+  - task:
+      type: text-generation
+      name: Logic
+    dataset:
+      name: ARC Challenge
+      type: ai2_arc
+    metrics:
+    - name: accuracy
+      type: exact_match
+      value: 86.0
+---
+
+# 🌌 Noir-Ultra (7B)
+
+<div align="center">
+
+[Noir Family](https://huggingface.co/collections/muverqqw/noir) | [GGUF Versions](https://huggingface.co/muverqqw/Noir-GGUF) | [Technical Report](#-noir-ultra-evaluation-dashboard)
+
+</div>
+
+**Noir-Ultra** is the elite 7-billion parameter model of the Noir series. It represents a breakthrough in training efficiency: where previous 7B iterations required 6 epochs to reach stability, **Noir-Ultra achieved superior results in just a single epoch**.
+
+This model is a "compact titan," delivering scientific reasoning and mathematical accuracy that rival much larger architectures.
+
+---
+
+## 🚀 The Ultra Advantage
+
+* 🧬 **Unrivaled STEM:** With a **91.0% score on SciQ**, it is a specialized tool for scientific inquiry.
+* 📐 **Mathematical Precision:** Scoring **84.0% on GSM8K**, it handles complex chains of thought with ease.
+* 🧠 **Logical Depth:** An ARC-Challenge score of **86.0%** places it at the top of its weight class for reasoning tasks.
+
+---
+
+## 📊 Evaluation Dashboard (Noir Ultra Report)
+
+Based on the latest evaluation, Noir-Ultra shows an exceptionally strong profile in technical domains:
+
+| Domain | Benchmark | Result (%) | Status |
+| :--- | :--- | :---: | :--- |
+| **STEM** | SciQ | **91.0%** | 🏆 Master |
+| **Logic** | ARC-C | **86.0%** | 🔥 Elite |
+| **Math** | GSM8K | **84.0%** | ✅ Advanced |
+| **Medicine** | MedQA | **65.0%** | 🩺 Competent |
+| **Physics** | MMLU-Physics| **70.0%** | 🧪 Specialist |
+
+
+
+---
+
+## 📦 Noir Model Family Matrix
+
+| Model | Parameters | Role | Key Strength |
+| :--- | :--- | :--- | :--- |
+| **Noir-Lightning** | 0.5B | The Pocket Assistant | Ultra-fast, runs on anything |
+| **Noir-Mini** | 1.5B | The Balanced Thinker | High speed with solid grammar |
+| **Noir-Standard** | 3B | The Versatile Workhorse | 65% GSM8K, perfect for 8GB VRAM |
+| **Noir-Ultra** | **7B** | **The Reasoning Master** | **91% SciQ & 84% Math** |
+| **Noir-Starlight** | 14B | The Galactic Intelligence | Deep logic & Expert-level STEM |
+
+---
+
+## 🛠 Quick Start (Transformers)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_name = "muverqqw/Noir-Ultra" 
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name, 
+    load_in_4bit=True, # Recommended for 8GB VRAM
+    device_map="auto"
+)
+```
+
+---
+
+### 👤 Credits
+* **Developer:** IceL1ghtning
+
+* **Architecture:** Qwen 2.5 (7B)
+
+* **Release:** 2026
+
+* **License:** Apache 2.0
+
+<div align="center">
+<sub>Efficiency meets intelligence. Built with passion for the open-source community.</sub>
+</div>