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
File size: 1,458 Bytes
b88c26d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | #!/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
|