Text Generation
PEFT
Safetensors
Transformers
English
German
Italian
gemma4
lora
mosaic-kg
knowledge-graph
webmaster
structured-output
alpine
tourism
conversational
Instructions to use cyberandy/Alpino-e4b-v01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cyberandy/Alpino-e4b-v01 with PEFT:
Task type is invalid.
- Transformers
How to use cyberandy/Alpino-e4b-v01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cyberandy/Alpino-e4b-v01") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cyberandy/Alpino-e4b-v01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use cyberandy/Alpino-e4b-v01 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cyberandy/Alpino-e4b-v01" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cyberandy/Alpino-e4b-v01", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cyberandy/Alpino-e4b-v01
- SGLang
How to use cyberandy/Alpino-e4b-v01 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 "cyberandy/Alpino-e4b-v01" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cyberandy/Alpino-e4b-v01", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "cyberandy/Alpino-e4b-v01" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cyberandy/Alpino-e4b-v01", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cyberandy/Alpino-e4b-v01 with Docker Model Runner:
docker model run hf.co/cyberandy/Alpino-e4b-v01
Commit History
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Note Alpino's role as the working demonstrator for MOSAIC-KG
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Update README.md
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Add model lineage section to model card (Gemma 4 E4B -> Alpino v0.1 SFT -> 20/20 AOOE capability floor)
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Add alpina.travel link with apartments in Lungau anchor
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Fix peft.task_type in adapter_config.json
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Update model card to emphasize small-model governance for agentic storefront
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Upload Alpino-e4b-v01 model adapter and model card
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initial commit
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