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
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ad7c73d 3817cd0 ad7c73d 3817cd0 ad7c73d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | {
"architectures": [
"ARLoopForCausalLM"
],
"attnres_block_size": 18,
"auto_map": {
"AutoConfig": "configuration_arloop.ARLoopConfig",
"AutoModelForCausalLM": "modeling_arloop.ARLoopForCausalLM"
},
"bos_token_id": 0,
"dtype": "bfloat16",
"embedding_scale": 1.0,
"eos_token_id": 0,
"head_dim": 96,
"hidden_size": 1536,
"intermediate_size": 4608,
"logit_softcap": null,
"loop_count": 3,
"max_position_embeddings": 4096,
"model_type": "arloop",
"num_attention_heads": 16,
"num_hidden_layers": 54,
"num_key_value_heads": 4,
"pad_token_id": 0,
"physical_layers": 18,
"qk_norm": true,
"rms_norm_eps": 1e-05,
"rope_condense_ratio": 1,
"rope_theta": 50000,
"sw_blocks": 3,
"tie_word_embeddings": true,
"transformers_version": "5.12.1",
"use_cache": true,
"vocab_size": 49152,
"torch_dtype": "bfloat16"
}
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