Instructions to use hzy00/ALiBi-151M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hzy00/ALiBi-151M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hzy00/ALiBi-151M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("hzy00/ALiBi-151M") model = AutoModelForCausalLM.from_pretrained("hzy00/ALiBi-151M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hzy00/ALiBi-151M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hzy00/ALiBi-151M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hzy00/ALiBi-151M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hzy00/ALiBi-151M
- SGLang
How to use hzy00/ALiBi-151M 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 "hzy00/ALiBi-151M" \ --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": "hzy00/ALiBi-151M", "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 "hzy00/ALiBi-151M" \ --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": "hzy00/ALiBi-151M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hzy00/ALiBi-151M with Docker Model Runner:
docker model run hf.co/hzy00/ALiBi-151M
- Xet hash:
- a78144b9a601e85e31a02f900ade6a7799563861c093dad7952e318f678ed1f3
- Size of remote file:
- 650 MB
- SHA256:
- b62c7a1669aa0fac1e3c94c7e5e6e08bc4c162a0a2586c7aa7baf8f16d2b16cd
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