Instructions to use LM-Parallel/standard-ref with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LM-Parallel/standard-ref with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LM-Parallel/standard-ref")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LM-Parallel/standard-ref") model = AutoModelForCausalLM.from_pretrained("LM-Parallel/standard-ref") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LM-Parallel/standard-ref with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LM-Parallel/standard-ref" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LM-Parallel/standard-ref", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LM-Parallel/standard-ref
- SGLang
How to use LM-Parallel/standard-ref 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 "LM-Parallel/standard-ref" \ --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": "LM-Parallel/standard-ref", "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 "LM-Parallel/standard-ref" \ --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": "LM-Parallel/standard-ref", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LM-Parallel/standard-ref with Docker Model Runner:
docker model run hf.co/LM-Parallel/standard-ref
- Xet hash:
- 9a3c4f834d6f2e3be665fb8cc7a03d1da6c7d682eb8a40bc2bb7916d9a7dbad7
- Size of remote file:
- 1.03 GB
- SHA256:
- 6abe6a39b66e665069a59cd7aa7814590890362069df97a152b3a7af29741e15
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