Text Generation
Transformers
ONNX
PyTorch
English
symbolic-decoder
aletheia
philosophical-agi
gnai-creator
Instructions to use gnai-creator/noesis-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gnai-creator/noesis-decoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="gnai-creator/noesis-decoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gnai-creator/noesis-decoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use gnai-creator/noesis-decoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gnai-creator/noesis-decoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gnai-creator/noesis-decoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/gnai-creator/noesis-decoder
- SGLang
How to use gnai-creator/noesis-decoder 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 "gnai-creator/noesis-decoder" \ --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": "gnai-creator/noesis-decoder", "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 "gnai-creator/noesis-decoder" \ --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": "gnai-creator/noesis-decoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use gnai-creator/noesis-decoder with Docker Model Runner:
docker model run hf.co/gnai-creator/noesis-decoder
Download model.onnx from gnai-creator/noesis-decoder: direct link, hf CLI and curl.
- Browser
- Download file 1.61 MB
-
https://huggingface.co/gnai-creator/noesis-decoder/resolve/main/model.onnx
- Command line
-
hf download hf://gnai-creator/noesis-decoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/gnai-creator/noesis-decoder/resolve/main/model.onnx
1.61 MB
- Xet hash:
- 1e77f6e7037b2ad7a518ea7c616ff0d59690c089a767b6578b2b3efb9edf9290
- Size of remote file:
- 1.61 MB
- SHA256:
- 1154ef7aefd95931fcfb7c882cac57d258b340c4971eb62394e69a8e54570370
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.