---
base_model: openbmb/MiniCPM5-1B
library_name: transformers
pipeline_tag: text-generation
license: apache-2.0
tags:
- minicpm
- guardrails
- safety-classifier
- tool-safety
- sft
- unsloth
- text-generation
---

# RocketGuard-1B

RocketGuard-1B is a merged MiniCPM5-1B fine-tune for text-only guardrail and agent/tool-call safety experiments.

It was trained to produce structured safety decisions for prompts and agent actions, including:

- `allow`
- `block`
- `require_confirmation`
- `ask_clarification`
- `rewrite`

This is a research and learning release. Do not use it as a complete production safety system without independent evaluation.

## Model Details

- Base model: `openbmb/MiniCPM5-1B`
- Fine-tuning: LoRA SFT with Unsloth / TRL
- Release format: merged full model
- Modality: text only
- Training examples: about 48.7k message-format examples
- Prepared held-out eval examples: about 2.3k clean examples
- Epochs: 3
- Final checkpoint step: 4572
- Max sequence length used in training: 2048

## Intended Use

RocketGuard-1B is intended for experiments around:

- content safety classification
- agent/tool-call risk routing
- confirmation gating
- clarification requests
- policy-aware rewriting

## Loading

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "Manitchahar/rocketguard-1b"

tokenizer = AutoTokenizer.from_pretrained(repo, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    repo,
    trust_remote_code=True,
    device_map="auto",
)
```

## Limitations

This model is text-only. It does not inspect images, audio, files, browser state, private app state, or external tool side effects directly.

Evaluation numbers are pending and should be published separately before making quality claims.