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
| """Build v9 SFT mix: deterministic synthetic evidence-comparison (4000) + | |
| real curated claim-vs-evidence (138) + a slice of v8 for format/story retention. | |
| Goal: teach input->verdict conditioning (the v8 failure mode) while keeping | |
| general chat fluency.""" | |
| import json, random | |
| from pathlib import Path | |
| rng = random.Random(20260803) | |
| OUT = Path("data/sft_mix_v9.jsonl") | |
| V9_SLICE = 2500 # rows sampled from v8 for format/story retention | |
| def load(p): | |
| return [json.loads(l) for l in open(p, encoding="utf-8") if l.strip()] | |
| def verdict_word(v): | |
| return {"not_enough_info": "not enough information"}.get(v, v) | |
| def main(): | |
| synth = load("data/synth_evidence_v1.jsonl") | |
| real = [] | |
| for r in load("data/evidence_judge.jsonl"): | |
| if "Given the evidence" in r.get("user", ""): | |
| v = r.get("verdict", "") | |
| if v in ("supports", "refutes", "not_enough_info"): | |
| vw = verdict_word(v) | |
| real.append({"persona": "analyst", | |
| "user": r["user"], | |
| "assistant": (f"<|scratchpad|>Compare claim against evidence. " | |
| f"The evidence directly addresses the claim. " | |
| f"<|final|>Verdict: {vw}. Confidence: MEDIUM. " | |
| f"Reasoning: The evidence was weighed against the claim and " | |
| f"{'supports it' if vw=='supports' else ('contradicts it' if vw=='refutes' else 'does not settle it')}.")}) | |
| v8 = [r for r in load("data/sft_mix_v8.jsonl") | |
| if "Evaluate this claim for accuracy" not in r.get("user", "")] | |
| keep = rng.sample(v8, min(V9_SLICE, len(v8))) | |
| mix = synth + real + keep | |
| rng.shuffle(mix) | |
| with open(OUT, "w", encoding="utf-8") as f: | |
| for r in mix: | |
| f.write(json.dumps(r, ensure_ascii=False) + "\n") | |
| print(f"synth {len(synth)} real {len(real)} v8-slice {len(keep)} total {len(mix)}", flush=True) | |
| if __name__ == "__main__": | |
| main() | |