Instructions to use GoofyLM/N2-Nemo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GoofyLM/N2-Nemo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GoofyLM/N2-Nemo")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GoofyLM/N2-Nemo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GoofyLM/N2-Nemo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GoofyLM/N2-Nemo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GoofyLM/N2-Nemo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GoofyLM/N2-Nemo
- SGLang
How to use GoofyLM/N2-Nemo 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 "GoofyLM/N2-Nemo" \ --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": "GoofyLM/N2-Nemo", "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 "GoofyLM/N2-Nemo" \ --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": "GoofyLM/N2-Nemo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GoofyLM/N2-Nemo with Docker Model Runner:
docker model run hf.co/GoofyLM/N2-Nemo
Download checkpoint-3/optimizer.pt from GoofyLM/N2-Nemo: direct link, hf CLI and curl.
- Browser
- Download file 31.6 MB
-
https://huggingface.co/GoofyLM/N2-Nemo/resolve/main/checkpoint-3/optimizer.pt
- Command line
-
hf download hf://GoofyLM/N2-Nemo/checkpoint-3/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/GoofyLM/N2-Nemo/resolve/main/checkpoint-3/optimizer.pt
31.6 MB
- Xet hash:
- b72112dc582dbdf1c015bebb7de3a7f66912688dc3510bdaa10b587a3327c2e9
- Size of remote file:
- 31.6 MB
- SHA256:
- eeefdc22c6136e431527bae9f0a4093f584b4710e0f83f6c68c519c256876189
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