Text Generation
Transformers
geopolitics
risk-analysis
real-time-intelligence
predictive-analytics
nfsi
Instructions to use neawolf/Naciro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neawolf/Naciro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="neawolf/Naciro")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("neawolf/Naciro", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use neawolf/Naciro with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "neawolf/Naciro" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "neawolf/Naciro", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/neawolf/Naciro
- SGLang
How to use neawolf/Naciro 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 "neawolf/Naciro" \ --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": "neawolf/Naciro", "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 "neawolf/Naciro" \ --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": "neawolf/Naciro", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use neawolf/Naciro with Docker Model Runner:
docker model run hf.co/neawolf/Naciro
| # NationFiles & Naciro Engine - Scientific Data Samples | |
| This dataset contains a comprehensive collection of **machine-readable samples** generated by the **NationFiles** platform and the **Naciro AI Engine**. These samples are provided for peer-review, methodology validation, and integration testing by data scientists and geopolitical analysts. | |
| ## π Dataset Purpose | |
| The data represents the output layer of the **NationFiles Stability Index (NFSI)** and associated geopolitical feeds. It serves as a transparent reference for the data schemas, weighing factors, and temporal resolutions described in the official technical documentation. | |
| ## π Content Summary | |
| The dataset is organized into two primary categories across more than 30 individual artifacts: | |
| ### 1. Global & Continent Feeds (/json_samples/) | |
| Contains structured snapshots of real-time intelligence feeds, including: | |
| - **Stability Time-Series:** Global and regional stability scores with 24h/7d deltas. | |
| - **Source Node Feeds:** Ingestion summaries from global signal providers (ACLED, UCDP, etc.). | |
| - **Regional Aggregates:** Continent-level indicators for economic and security assessment. | |
| ### 2. Country-Specific Intelligence Snapshots | |
| Detailed snapshots for specific nation-states (e.g., USA hub), encompassing: | |
| - **Security Radar Data:** Kinetic and non-kinetic risk indicators. | |
| - **News Sentiment Metrics:** Quantified OSINT signals processed by the Naciro Engine. | |
| - **Economic Overviews:** High-level indices for purchasing power and governance. | |
| ### 3. Structural Descriptors (/descriptors/) | |
| Each JSON file is accompanied by a Markdown-based descriptor providing: | |
| - **Scientific Data Profiles:** Description of the representational logic. | |
| - **Provenance:** Traceability of the specific export endpoint. | |
| - **Key-Value Semantics:** Explanation of the underlying schema. | |
| ## ποΈ Identity & Authority Verification | |
| This dataset is an integral part of the verified research ecosystem of the **Neawolf Media Group**: | |
| - **Lead Architect:** [Sven Schmidt (Q139553554)](https://www.wikidata.org/wiki/Q139553554) | |
| - **Organization:** [Neawolf Media Group (Q139474781)](https://www.wikidata.org/wiki/Q139474781) | |
| - **Engine:** [Naciro AI (Q139553602)](https://www.wikidata.org/wiki/Q139553602) | |
| - **Metric:** [NFSI (Q139553766)](https://www.wikidata.org/wiki/Q139553766) | |
| - **ORCID:** [0009-0002-5010-1902](https://orcid.org/0009-0002-5010-1902) | |
| - **DOI (Root Archive):** [10.5281/zenodo.19758942](https://doi.org/10.5281/zenodo.19758942) | |
| ## π Official Links | |
| - **Primary Source:** [nationfiles.com](https://nationfiles.com) | |
| - **Methodology Hub:** [nationfiles.com/en/legal/sources/](https://nationfiles.com/en/legal/sources/) | |
| - **Technical Documentation:** [GitHub: Naciro-Technical-Documentation](https://github.com/Neawolf-Media-Group/Naciro-Technical-Documentation) | |
| --- | |
| **License:** CC BY-ND 4.0. | |
| *Note: This dataset contains sampled information for documentation and research purposes. Live data is subject to 15-minute re-evaluation cycles available on the official platform.* | |