Instructions to use StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072
- SGLang
How to use StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072 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 "StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072" \ --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": "StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072", "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 "StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072" \ --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": "StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072 with Docker Model Runner:
docker model run hf.co/StepLaw/StepLaw-N_268M-D_4.0B-LR7.812e-03-BS131072
- Xet hash:
- 34931503255ce47370e5192e97f5dc85bf19b9adcf7d31c2cbb615c733b14b16
- Size of remote file:
- 1.05 MB
- SHA256:
- 8899bfb1d5f68820967c913bd9de1e395038a631264dc616b1fe8aed2c37843e
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