Instructions to use iohadrubin/rpt-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iohadrubin/rpt-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="iohadrubin/rpt-1b")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("iohadrubin/rpt-1b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use iohadrubin/rpt-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "iohadrubin/rpt-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "iohadrubin/rpt-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/iohadrubin/rpt-1b
- SGLang
How to use iohadrubin/rpt-1b 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 "iohadrubin/rpt-1b" \ --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": "iohadrubin/rpt-1b", "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 "iohadrubin/rpt-1b" \ --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": "iohadrubin/rpt-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use iohadrubin/rpt-1b with Docker Model Runner:
docker model run hf.co/iohadrubin/rpt-1b
- Xet hash:
- 017015f3344d58a4fae9005928f786da68be78582f96a599bf3a6722dc21ccd0
- Size of remote file:
- 2.95 GB
- SHA256:
- 6bd76d6fafe2dd73facb0e698f95585797be32325eb8619622401277fece5446
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