初始化项目，由ModelHub XC社区提供模型

Model: OrionLLM/Nebula
Source: Original Platform

README.md

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+---
+license: apache-2.0
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- nebula
+- reasoning
+- text-generation
+- transformers
+---
+
+# Nebula
+
+<p align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/685ea8ff7b4139b6845ce395/YF0kEDYMGJhcM3Lbl2EOD.png" alt="Nebula logo" width="100">
+</p>
+
+## 1. Introduction
+**Nebula** is a **320M-parameter** generalist Small Reasoning Model trained on **200B+ tokens**, designed for edge AI and on-device deployment.
+
+Nebula is designed to deliver an unusually strong balance of **memory**, **general reasoning**, **math**, and **retrieval-friendly behavior** for its size class, aiming to outperform many small models of a similar parameter range on non-code, industry-style benchmarks.
+
+## 2. Reasoning style
+Nebula’s reasoning traces use an intentionally compact style with **dense, short, frequently non-verbal sentences**, optimized for efficiency under limited model capacity.
+
+Traces use the following stenographic notation integrated into special tokens:
+
+### Logical markers
+
+| Token | Meaning | Usage |
+| ----- | ------- | ----- |
+| **→** | derivation / implication | For very short causal/logical flow |
+| **↺** | iterative return / refinement loop | For backtracking, reconsidering priors, RAG re-querying |
+| **?** | uncertainty/questions to resolve | Can be appended to short expressions/words, not only interrogatives |
+| **!/※** | insight/breakthroughs | Emphatic mark for knowledge discovery |
+| **≈** | approximation/estimates | For intermediary hypothesis / uncertain preliminary statements |
+| **∴** | therefore / final step | Use sparingly to mark stable conclusions |
+
+### Uncertainty
+
+| Token | Meaning | Usage |
+| ----- | ------- | ----- |
+| **●** | high confidence | well-supported empirical/theoretical ground; “anchor points.” |
+| **◐** | medium/partial confidence | incomplete data; plausible but unverified links |
+| **○** | low confidence | speculation, missing context, weak inference chain |
+| **⚠** | bias/premise risk | domain mismatch, cultural assumptions, language-switch artifacts |
+| **?maybe?** | soft speculation | marks tentative ideas, branches that might collapse later |
+
+### Verification process
+
+| Token | Meaning | Usage |
+| ----- | ------- | ----- |
+| **☐** | unverified hypothesis | raw claim, no cross-check yet |
+| **☑** | intermediate verification | one source/argument supports it |
+| **✓** | confirmed/validated | multiple independent supports (●-level) |
+
+This reasoning format is designed to remain expressive while being lightweight enough for a small model.
+
+## 3. Fine-Tuning/RL
+Nebula has been successfully fine-tuned for a variety of tasks
+
+Because Nebula is a reasoning-oriented model, it is expected to train well with reinforcement learning methods such as **GRPO**, both for **verifiable tasks** (with objective rewards) and for subjective tasks using an **LLM-as-a-judge**.
+
+## 4. Benchmarks
+
+| Model | MMLU |
+|------|-----:|
+| **Nebula** | **40.0** |
+| SmolLM2-360M | 35.8 |
+| Gemma 3 270M (IT) | 26.5 |
+| Granite-4.0-H-350M | 36.21 |