Text Generation
Transformers
PyTorch
English
ramo
Mixture of Experts
mixture-of-experts
reasoning
chain-of-thought
cot
system-2-thinking
nlp
conversational
instruct
sft
dpo
grpo
rlhf
math
logic
scientific-reasoning
efficient
low-resource
data-efficient
from-scratch
pretrained
0.6b
nano-model
small-model
european-ai
austria
independent-research
arxiv
python
coding
step-by-step
self-correction
hallucination-reduction
educational
research
benchmark
thinking-mode
mental-models
deductive-reasoning
analytical
problem-solving
custom_code
Instructions to use noeum/noeum-1-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noeum/noeum-1-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="noeum/noeum-1-nano", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("noeum/noeum-1-nano", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use noeum/noeum-1-nano with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "noeum/noeum-1-nano" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "noeum/noeum-1-nano", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/noeum/noeum-1-nano
- SGLang
How to use noeum/noeum-1-nano 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 "noeum/noeum-1-nano" \ --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": "noeum/noeum-1-nano", "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 "noeum/noeum-1-nano" \ --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": "noeum/noeum-1-nano", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use noeum/noeum-1-nano with Docker Model Runner:
docker model run hf.co/noeum/noeum-1-nano
- Xet hash:
- 91da2206467de17de68f6f367ea0ae5057cc9aa0cd0f76f632d5625995e32f97
- Size of remote file:
- 2.41 GB
- SHA256:
- 5255d15d18da9cc49d5ddce6b8e79bad5676c4326e969faee5dd9937ac145d73
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