Text Generation
PEFT
Safetensors
llama
grpo
reinforcement-learning
devops
incident-response
openenv
unsloth
conversational
Instructions to use Arijit-07/aria-devops-llama8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Arijit-07/aria-devops-llama8b with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio
How to use Arijit-07/aria-devops-llama8b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Arijit-07/aria-devops-llama8b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Arijit-07/aria-devops-llama8b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Arijit-07/aria-devops-llama8b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Arijit-07/aria-devops-llama8b", max_seq_length=2048, )
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base_model: unsloth/Meta-Llama-3.1-8B-Instruct
library_name: peft
pipeline_tag: text-generation
tags:
- grpo
- reinforcement-learning
- devops
- incident-response
- openenv
- unsloth
---
# ARIA — DevOps Incident Response Agent
### Llama-3.1-8B fine-tuned with GRPO
Trained on the [ARIA DevOps Incident Response](https://huggingface.co/spaces/Arijit-07/devops-incident-response)
live RL environment using GRPO.
## Training Results
| Task | Baseline | Fine-tuned | Improvement |
|---|---|---|---|
| easy | 0.320 | 0.685 | **+0.365** |
| medium | 0.050 | 0.378 | **+0.328** |
| hard | 0.190 | 0.869 | **+0.679** |
| bonus | 0.152 | 0.682 | **+0.530** |

## Setup
- Algorithm: GRPO
- Base: Llama-3.1-8B-Instruct
- LoRA rank: 32, alpha: 64
- Episodes: 160 (40 per task)
- GPU: NVIDIA L4, 162 minutes
- Framework: Unsloth + HuggingFace TRL
## Links
- Environment: https://huggingface.co/spaces/Arijit-07/devops-incident-response
- GitHub: https://github.com/Twilight-13/devops-incident-response |