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
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.