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