Text Generation
Transformers
PyTorch
English
burt-imma
custom-architecture
matrix-memory
equilibrium-propagation
cifg
sovereign
snapkitty
no-backprop
formal-verification
lean4
agents
python
Instructions to use Snapkitty/burt-imma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Snapkitty/burt-imma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Snapkitty/burt-imma")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Snapkitty/burt-imma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Snapkitty/burt-imma with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Snapkitty/burt-imma" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Snapkitty/burt-imma", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Snapkitty/burt-imma
- SGLang
How to use Snapkitty/burt-imma 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 "Snapkitty/burt-imma" \ --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": "Snapkitty/burt-imma", "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 "Snapkitty/burt-imma" \ --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": "Snapkitty/burt-imma", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Snapkitty/burt-imma with Docker Model Runner:
docker model run hf.co/Snapkitty/burt-imma
Download scripts/burt-imma-gate from Snapkitty/burt-imma: direct link, hf CLI and curl.
- Browser
- Download file 563 Bytes
-
https://huggingface.co/Snapkitty/burt-imma/resolve/main/scripts/burt-imma-gate
- Command line
-
hf download hf://Snapkitty/burt-imma/scripts/burt-imma-gate
-
curl -L -o burt-imma-gate https://huggingface.co/Snapkitty/burt-imma/resolve/main/scripts/burt-imma-gate
563 Bytes
| # BURT-IMMA Protected Execution Gate | |
| # Shell wrapper for burt_imma_gate.py | |
| # Contact: jessica@collectivekitty.com | |
| SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" | |
| REPO_ROOT="$(dirname "$SCRIPT_DIR")" | |
| export BURT_IMMA_REPO_ROOT="$REPO_ROOT" | |
| PYTHON_GATE="$REPO_ROOT/burt_imma_gate.py" | |
| if [ ! -f "$PYTHON_GATE" ]; then | |
| echo "ERROR: Python gate not found at $PYTHON_GATE" | |
| exit 3 | |
| fi | |
| if ! command -v python3 &> /dev/null; then | |
| echo "ERROR: python3 not found in PATH" | |
| exit 3 | |
| fi | |
| exec python3 "$PYTHON_GATE" "$@" | |