Instructions to use osunlp/ARLoop-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osunlp/ARLoop-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="osunlp/ARLoop-0.6B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("osunlp/ARLoop-0.6B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use osunlp/ARLoop-0.6B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "osunlp/ARLoop-0.6B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "osunlp/ARLoop-0.6B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/osunlp/ARLoop-0.6B
- SGLang
How to use osunlp/ARLoop-0.6B 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 "osunlp/ARLoop-0.6B" \ --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": "osunlp/ARLoop-0.6B", "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 "osunlp/ARLoop-0.6B" \ --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": "osunlp/ARLoop-0.6B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use osunlp/ARLoop-0.6B with Docker Model Runner:
docker model run hf.co/osunlp/ARLoop-0.6B
Align model card introduction with ARLoop-1.2B
Browse files
README.md
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# ARLoop-0.6B
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ARLoop is a
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contains the final checkpoint of the
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It is a **base pretrained model** for text completion,
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Training code: [ykyaol7/ARLoop](https://github.com/ykyaol7/ARLoop).
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# ARLoop-0.6B
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ARLoop is a fully-open pretrained looped transformer with attention residuals. This release
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contains the final checkpoint of the 0.6B, 180B-token training run.
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It is a **base pretrained model**, intended for text completion, which can be used for mid-training and post-training.
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Training code: [ykyaol7/ARLoop](https://github.com/ykyaol7/ARLoop).
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