Text Generation
Transformers
English
Polish
jfp-aligned
jfp
deterministic
multi-agent
governance
auditable-ai
protocol
viki
tool-use
qwen2
Instructions to use jarohullowicki/Jjfp-core-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jarohullowicki/Jjfp-core-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jarohullowicki/Jjfp-core-v1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jarohullowicki/Jjfp-core-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jarohullowicki/Jjfp-core-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jarohullowicki/Jjfp-core-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jarohullowicki/Jjfp-core-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jarohullowicki/Jjfp-core-v1
- SGLang
How to use jarohullowicki/Jjfp-core-v1 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 "jarohullowicki/Jjfp-core-v1" \ --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": "jarohullowicki/Jjfp-core-v1", "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 "jarohullowicki/Jjfp-core-v1" \ --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": "jarohullowicki/Jjfp-core-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jarohullowicki/Jjfp-core-v1 with Docker Model Runner:
docker model run hf.co/jarohullowicki/Jjfp-core-v1
|
Download README.md from jarohullowicki/Jjfp-core-v1: direct link, hf CLI and curl.
- Browser
- Download file 2.76 kB
-
https://huggingface.co/jarohullowicki/Jjfp-core-v1/resolve/eec860fbf7c9d77b9f11b260d72fb64ab3f3080f/README.md
- Command line
-
hf download hf://jarohullowicki/Jjfp-core-v1@eec860fbf7c9d77b9f11b260d72fb64ab3f3080f/README.md
-
curl -L -o README.md https://huggingface.co/jarohullowicki/Jjfp-core-v1/resolve/eec860fbf7c9d77b9f11b260d72fb64ab3f3080f/README.md
2.76 kB
| license: cc-by-nc-4.0 | |
| language: | |
| - en | |
| - pl | |
| base_model: Qwen/Qwen2.5-7B-Instruct | |
| pipeline_tag: text-generation | |
| library_name: transformers | |
| tags: | |
| - jfp | |
| - deterministic | |
| - multi-agent | |
| - governance | |
| - auditable-ai | |
| - protocol | |
| - viki | |
| - tool-use | |
| - qwen2 | |
| # JFP-Core-v1 — Jaro Flash Protocol Aligned Model | |
| ## What is this? | |
| JFP-Core-v1 is the first model configuration aligned with the **Jaro Flash Protocol (JFP) v16E.0.0** — a deterministic multi-agent AI execution framework developed by Jarosław Kuchta. | |
| This is not a standard language model. It is a **protocol-governed AI engine** designed for auditable, traceable, and reproducible AI applications. | |
| ## Key Properties | |
| - **Deterministic execution** — consistent outputs for structured inputs | |
| - **JFP constitutional layer** — built-in rules that cannot be overridden by user prompts | |
| - **Reduced hallucination** — refusal protocol replaces confabulation | |
| - **Audit trail ready** — every output is traceable and explainable | |
| - **Anti-drift design** — behavior stays within defined protocol boundaries | |
| - **VOQL compatible** — native support for VIKI Operational Query Language | |
| ## Intended Use | |
| - Auditable enterprise AI pipelines | |
| - Multi-agent orchestration systems | |
| - Compliance-sensitive applications (legal, medical, financial) | |
| - JFP-standard compatible tooling | |
| ## Not Intended For | |
| - General-purpose chat | |
| - Creative/open-ended generation without protocol constraints | |
| - Applications requiring unpredictable or exploratory outputs | |
| ## Base Model | |
| Built as a fine-tune configuration for **Qwen/Qwen2.5-7B-Instruct**. | |
| ## Tools | |
| This model includes a native tool specification. See `tools.json` in this repository. | |
| Supported tools: | |
| - `code_execution` — sandboxed Python/bash execution | |
| - `file_operations` — read/write within JFP boundaries | |
| - `voql_query` — VIKI Operational Query Language queries | |
| - `agent_dispatch` — sub-agent communication within VIKI ecosystem | |
| - `audit_log` — immutable action logging | |
| - `api_call` — external REST API calls (whitelist only) | |
| - `jfp_validate` — schema validation against JFP standard | |
| ## Limitations | |
| - Requires JFP-compliant input format for optimal performance | |
| - Not designed for open-ended creative tasks | |
| - Commercial use requires separate licensing agreement | |
| ## Protocol | |
| Built on **JFP v16E.0.0** — part of the VIKI ecosystem. | |
| Author: Jarosław Kuchta | [GitHub](https://github.com/etechvictoria-ui) | |
| ## License | |
| cc-by-nc-4.0 — Free for non-commercial use. | |
| Commercial licensing: contact the author. | |
| ## Citation | |
| ```bibtex | |
| @misc{kuchta2026jfp, | |
| author = {Jarosław Kuchta}, | |
| title = {Jaro Flash Protocol (JFP) v16E.0.0}, | |
| year = {2026}, | |
| publisher = {Hugging Face}, | |
| url = {https://huggingface.co/jarohullowicki/Jjfp-core-v1} | |
| } | |
| ``` |