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
| #!/bin/bash | |
| # BURT-IMMA Node Authorization Verification | |
| # 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 "[1/5] Locating authorization record..." | |
| if [ ! -f "$SOVEREIGN_DIR/authorization.json" ]; then | |
| echo "ERROR: Authorization record not found" | |
| exit 2 | |
| fi | |
| echo " Authorization record found" | |
| echo "[2/5] Locating node identity..." | |
| if [ ! -f "$SOVEREIGN_DIR/node.json" ]; then | |
| echo "ERROR: Node identity not found" | |
| exit 2 | |
| fi | |
| echo " Node identity found" | |
| echo "[3/5] Parsing authorization record..." | |
| STATUS=$(grep 'authorization_status' "$SOVEREIGN_DIR/authorization.json" | head -1 | sed 's/.*"authorization_status": "\([^"]*\)".*/\1/') | |
| REVOKED=$(grep 'revocation_status' "$SOVEREIGN_DIR/authorization.json" | head -1 | sed 's/.*"revocation_status": "\([^"]*\)".*/\1/') | |
| echo " Status: $STATUS" | |
| echo "[4/5] Validating authorization status..." | |
| if [ "$STATUS" != "ACTIVE" ]; then | |
| echo " Status is $STATUS (not authorized)" | |
| exit 1 | |
| fi | |
| echo " Status is ACTIVE" | |
| if [ "$REVOKED" != "ACTIVE" ]; then | |
| echo " Revocation status is $REVOKED" | |
| exit 1 | |
| fi | |
| echo " Not revoked" | |
| echo "[5/5] Verified." | |
| echo "" | |
| echo "==========================================" | |
| echo "AUTHORIZATION_STATUS: VALID" | |
| echo "==========================================" | |
| exit 0 | |