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
File size: 4,094 Bytes
70a0a60 | 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 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 | """Full-project backup to Hugging Face (continuity snapshot).
Pushes the entire workspace (code, data, notes, pipeline, checkpoints) to
FerrellSyntheticIntelligence/fsi-anomaly so work can continue on another
machine. Skips .venv and python caches. Resume-safe: a local manifest
(logs/hf_backup_manifest.json) records uploaded files by sha256, and files
already present on the Hub are skipped, so re-running after an interruption
continues where it stopped. Progress is visible per commit.
Usage:
HF_TOKEN=hf_xxx .venv/bin/python hf_backup.py # everything
HF_TOKEN=hf_xxx .venv/bin/python hf_backup.py --stage ckpt # checkpoints only
"""
import argparse
import hashlib
import json
import os
import sys
from pathlib import Path
from huggingface_hub import CommitOperationAdd, HfApi
HERE = Path(__file__).resolve().parent
EXCLUDED_DIRS = {".venv", "__pycache__", ".pytest_cache"}
EXCLUDED_SUFFIXES = {".pyc"}
MANIFEST = HERE / "logs" / "hf_backup_manifest.json"
BATCH_FILES = 100
BATCH_BYTES = 800_000_000 # ~800MB per commit (safer on tablet network)
def sha256(path: Path) -> str:
h = hashlib.sha256()
with open(path, "rb") as f:
for chunk in iter(lambda: f.read(1 << 20), b""):
h.update(chunk)
return h.hexdigest()
def iter_files(stage: str):
for p in sorted(HERE.rglob("*")):
if not p.is_file():
continue
rel = p.relative_to(HERE).as_posix()
parts = rel.split("/")
if any(part in EXCLUDED_DIRS for part in parts):
continue
if p.suffix in EXCLUDED_SUFFIXES:
continue
if rel == "logs/hf_backup_manifest.json":
continue
if stage == "small" and parts[0] == "ckpt":
continue
if stage == "ckpt" and parts[0] != "ckpt":
continue
yield rel, p
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--repo", default="FerrellSyntheticIntelligence/fsi-anomaly")
ap.add_argument("--stage", choices=["all", "small", "ckpt"], default="all")
args = ap.parse_args()
token = os.environ.get("HF_TOKEN")
if not token:
sys.exit("HF_TOKEN env var required")
api = HfApi(token=token)
try:
api.repo_info(args.repo, repo_type="model")
print(f"repo exists: {args.repo}", flush=True)
except Exception:
api.create_repo(args.repo, private=True, repo_type="model")
print(f"created repo: {args.repo} (private)", flush=True)
manifest = {}
if MANIFEST.exists():
try:
manifest = json.loads(MANIFEST.read_text())
except json.JSONDecodeError:
manifest = {}
remote = set(api.list_repo_files(args.repo, repo_type="model"))
print(f"remote files already present: {len(remote)}", flush=True)
ops = []
batch_bytes = 0
n_uploaded = 0
n_skipped = 0
def flush(reason):
nonlocal ops, batch_bytes, n_uploaded
if not ops:
return
api.create_commit(
repo_id=args.repo,
operations=ops,
commit_message=f"backup {args.stage}: {len(ops)} files ({reason})",
repo_type="model",
)
for op in ops:
manifest[op.path_in_repo] = sha256(Path(op.path_or_fileobj))
MANIFEST.write_text(json.dumps(manifest, indent=0))
n_uploaded += len(ops)
print(f"committed {len(ops)} files -> {n_uploaded} total ({reason})", flush=True)
ops = []
batch_bytes = 0
for rel, p in iter_files(args.stage):
if rel in remote or manifest.get(rel) == sha256(p):
n_skipped += 1
continue
ops.append(CommitOperationAdd(path_in_repo=rel, path_or_fileobj=str(p)))
batch_bytes += p.stat().st_size
if len(ops) >= BATCH_FILES or batch_bytes >= BATCH_BYTES:
flush("batch")
flush("final")
print(f"DONE stage={args.stage}: uploaded={n_uploaded} skipped={n_skipped}", flush=True)
print(f"repo: https://huggingface.co/{args.repo}", flush=True)
if __name__ == "__main__":
main()
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