Instructions to use FerrellSyntheticIntelligence/fsi-anomaly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use FerrellSyntheticIntelligence/fsi-anomaly with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf FerrellSyntheticIntelligence/fsi-anomaly # Run inference directly in the terminal: llama cli -hf FerrellSyntheticIntelligence/fsi-anomaly
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf FerrellSyntheticIntelligence/fsi-anomaly # Run inference directly in the terminal: llama cli -hf FerrellSyntheticIntelligence/fsi-anomaly
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf FerrellSyntheticIntelligence/fsi-anomaly # Run inference directly in the terminal: ./llama-cli -hf FerrellSyntheticIntelligence/fsi-anomaly
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf FerrellSyntheticIntelligence/fsi-anomaly # Run inference directly in the terminal: ./build/bin/llama-cli -hf FerrellSyntheticIntelligence/fsi-anomaly
Use Docker
docker model run hf.co/FerrellSyntheticIntelligence/fsi-anomaly
- LM Studio
- Jan
- Ollama
How to use FerrellSyntheticIntelligence/fsi-anomaly with Ollama:
ollama run hf.co/FerrellSyntheticIntelligence/fsi-anomaly
- Unsloth Desktop
- Docker Model Runner
How to use FerrellSyntheticIntelligence/fsi-anomaly with Docker Model Runner:
docker model run hf.co/FerrellSyntheticIntelligence/fsi-anomaly
- Lemonade
How to use FerrellSyntheticIntelligence/fsi-anomaly with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull FerrellSyntheticIntelligence/fsi-anomaly
Run and chat with the model
lemonade run user.fsi-anomaly-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
| """Publish hf_repo to Hugging Face. | |
| 1. Login: huggingface-cli login (or set HF_TOKEN) | |
| 2. Run: .venv/bin/python hf_upload.py --repo YOUR_ORG/tiny-liquid-analyst | |
| Creates the repo if missing, uploads every file in hf_repo/, and prints the | |
| model page URL. Requires huggingface_hub (installed). | |
| """ | |
| import argparse | |
| import sys | |
| from pathlib import Path | |
| from huggingface_hub import HfApi | |
| def main(): | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--repo", default="YOUR_ORG/tiny-liquid-analyst", | |
| help="HF repo id, e.g. yourname/tiny-liquid-analyst") | |
| ap.add_argument("--dir", default="hf_repo") | |
| ap.add_argument("--private", action="store_true", help="create as private repo") | |
| args = ap.parse_args() | |
| if args.repo.startswith("YOUR_ORG"): | |
| sys.exit("set --repo to your HF repo id (e.g. yourname/tiny-liquid-analyst)") | |
| api = HfApi() | |
| try: | |
| api.repo_info(args.repo) | |
| print(f"repo exists: {args.repo}") | |
| except Exception: | |
| api.create_repo(args.repo, private=args.private, repo_type="model") | |
| print(f"created repo: {args.repo}") | |
| files = sorted(Path(args.dir).rglob("*")) | |
| files = [f for f in files if f.is_file() and f.name not in (".DS_Store",)] | |
| paths = [str(f) for f in files] | |
| api.upload_folder(folder_path=args.dir, repo_id=args.repo, repo_type="model") | |
| print(f"uploaded {len(paths)} files -> https://huggingface.co/{args.repo}") | |
| print("next: edit the model card link in hf_repo/README.md and re-upload, or set it via the web UI.") | |
| if __name__ == "__main__": | |
| main() | |