Instructions to use ethicalabs/Kurtis-EON1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethicalabs/Kurtis-EON1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ethicalabs/Kurtis-EON1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ethicalabs/Kurtis-EON1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ethicalabs/Kurtis-EON1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ethicalabs/Kurtis-EON1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ethicalabs/Kurtis-EON1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ethicalabs/Kurtis-EON1
- SGLang
How to use ethicalabs/Kurtis-EON1 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 "ethicalabs/Kurtis-EON1" \ --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": "ethicalabs/Kurtis-EON1", "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 "ethicalabs/Kurtis-EON1" \ --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": "ethicalabs/Kurtis-EON1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ethicalabs/Kurtis-EON1 with Docker Model Runner:
docker model run hf.co/ethicalabs/Kurtis-EON1
SFT/Alignment - Phase 007-06-MLP8: ethicalabs/Kurtis-EON1-SFT Mix (1 epoch)
#9
by mrs83 - opened
Errata corrige: that's v0.7.6 not v0.7.5. v0.7.5 was still on Finetome
mrs83 changed discussion title from SFT/Alignment - Phase 007-05-MLP8: ethicalabs/Kurtis-EON1-SFT Mix (1 epoch) to SFT/Alignment - Phase 007-06-MLP8: ethicalabs/Kurtis-EON1-SFT Mix (1 epoch)
Look, linear GPU MEM! ๐ Just running an lm_eval with batch_size=16 on the new architecture.
Notice the orange line on the left. That is a perfectly flat, constant allocation of ~15GB out of 96GB, while compute (blue line) is pinned at 100%.
By shifting to a custom 3-Pass Triton kernel the memory footprint now scales linearly, allowing us to hold massive batch sizes and long contexts entirely in memory without triggering PyTorch's garbage collection or OOMs.