Instructions to use supreme-lab/ai-in-the-loop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use supreme-lab/ai-in-the-loop with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="supreme-lab/ai-in-the-loop")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("supreme-lab/ai-in-the-loop", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use supreme-lab/ai-in-the-loop with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "supreme-lab/ai-in-the-loop" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "supreme-lab/ai-in-the-loop", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/supreme-lab/ai-in-the-loop
- SGLang
How to use supreme-lab/ai-in-the-loop with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "supreme-lab/ai-in-the-loop" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "supreme-lab/ai-in-the-loop", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "supreme-lab/ai-in-the-loop" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "supreme-lab/ai-in-the-loop", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use supreme-lab/ai-in-the-loop with Docker Model Runner:
docker model run hf.co/supreme-lab/ai-in-the-loop
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README.md
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This repository contains **instruction-tuned large language models (LLMs)** designed for **real-time scam detection, conversational scam-baiting, and privacy-preserving federated learning**.
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The models are trained and evaluated as part of the paper:
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**[AI-in-the-Loop: Privacy Preserving Real-Time Scam Detection and Conversational Scambaiting by Leveraging LLMs and Federated Learning](https://
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This repository contains **instruction-tuned large language models (LLMs)** designed for **real-time scam detection, conversational scam-baiting, and privacy-preserving federated learning**.
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The models are trained and evaluated as part of the paper:
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**[AI-in-the-Loop: Privacy Preserving Real-Time Scam Detection and Conversational Scambaiting by Leveraging LLMs and Federated Learning](https://supreme-lab.github.io/ai-in-the-loop/)**
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