Instructions to use LumiOpen/Viking-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LumiOpen/Viking-13B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LumiOpen/Viking-13B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LumiOpen/Viking-13B") model = AutoModelForCausalLM.from_pretrained("LumiOpen/Viking-13B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LumiOpen/Viking-13B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LumiOpen/Viking-13B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LumiOpen/Viking-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LumiOpen/Viking-13B
- SGLang
How to use LumiOpen/Viking-13B 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 "LumiOpen/Viking-13B" \ --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": "LumiOpen/Viking-13B", "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 "LumiOpen/Viking-13B" \ --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": "LumiOpen/Viking-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LumiOpen/Viking-13B with Docker Model Runner:
docker model run hf.co/LumiOpen/Viking-13B
Could you create a GGUF-version of this base-model?
This base-model training seems to be finished? So could you create a GGUF-version of it?
This base-model training seems to be finished? So could you create a GGUF-version of it?
You can try to create gguf by yourself because support for Viking pre-tokenizer was added to llama.cpp:
This base-model training seems to be finished? So could you create a GGUF-version of it?
Created main quants for Viking 13b and Viking 7b. You can find them at my HF page.
Great Nikolay! Will you make them available through Ollama at some point? I’m hoping they update their llama.cpp soon so we can use Viking models with it.
Great Nikolay! Will you make them available through Ollama at some point? I’m hoping they update their llama.cpp soon so we can use Viking models with it.
I tried to upload Viking 7b to ollama's online database but encountered this unfixed issue: https://github.com/ollama/ollama/issues/2155