Text Generation
Transformers
PyTorch
English
burt-imma
custom-architecture
matrix-memory
equilibrium-propagation
cifg
sovereign
snapkitty
no-backprop
formal-verification
lean4
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")# 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
| # BURT-IMMA Clone Integrity Verification | |
| # Verifies that a clone matches the official release. | |
| # Contact: jessica@collectivekitty.com | |
| set -e | |
| SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" | |
| REPO_ROOT="$(dirname "$SCRIPT_DIR")" | |
| SOVEREIGN_DIR="$REPO_ROOT/sovereign" | |
| echo "========================================" | |
| echo "BURT-IMMA CLONE INTEGRITY VERIFICATION" | |
| echo "========================================" | |
| echo "" | |
| if [ ! -f "$SOVEREIGN_DIR/release.json" ]; then | |
| echo "ERROR: sovereign/release.json not found" | |
| exit 1 | |
| fi | |
| echo "[1] Reading release metadata..." | |
| RELEASE_FILE="$SOVEREIGN_DIR/release.json" | |
| GIT_COMMIT=$(grep '"git_commit"' "$RELEASE_FILE" | head -1 | cut -d'"' -f4) | |
| VERSION=$(grep '"release_version"' "$RELEASE_FILE" | head -1 | cut -d'"' -f4) | |
| echo " Version: $VERSION" | |
| echo "" | |
| echo "[2] Verifying git commit..." | |
| CURRENT_COMMIT=$(cd "$REPO_ROOT" && git rev-parse HEAD 2>/dev/null || echo "") | |
| if [ -z "$CURRENT_COMMIT" ]; then | |
| echo " Not a git repository" | |
| exit 2 | |
| fi | |
| if [ "$CURRENT_COMMIT" != "$GIT_COMMIT" ]; then | |
| echo " Commit mismatch" | |
| echo " Expected: $GIT_COMMIT" | |
| echo " Actual: $CURRENT_COMMIT" | |
| exit 1 | |
| fi | |
| echo " Commit matches release" | |
| echo "" | |
| echo "========================================" | |
| echo "STATUS: INTEGRITY_VERIFIED" | |
| echo "========================================" | |
| echo "" | |
| exit 0 | |