Instructions to use Malte0621/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Malte0621/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Malte0621/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Malte0621/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Malte0621/test with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Malte0621/test" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Malte0621/test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Malte0621/test
- SGLang
How to use Malte0621/test 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 "Malte0621/test" \ --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": "Malte0621/test", "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 "Malte0621/test" \ --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": "Malte0621/test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Malte0621/test with Docker Model Runner:
docker model run hf.co/Malte0621/test
Download model.gguf.6M from Malte0621/test: direct link, hf CLI and curl.
- Browser
- Download file 31.2 MB
-
https://huggingface.co/Malte0621/test/resolve/979738b12f7baeaace8da9aa037816a172d2b523/model.gguf.6M
- Command line
-
hf download hf://Malte0621/test@979738b12f7baeaace8da9aa037816a172d2b523/model.gguf.6M
-
curl -L -o model.gguf.6M https://huggingface.co/Malte0621/test/resolve/979738b12f7baeaace8da9aa037816a172d2b523/model.gguf.6M
31.2 MB
- Xet hash:
- 4e73e939af69b09e85ae3e8f6556c33c2d837405d3211a774a2e5b720f42a5bd
- Size of remote file:
- 31.2 MB
- SHA256:
- 70d887e5ed62bbaebef7699ef437d1a566485ad00add3ae713b323f4ab27b224
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