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")# pip install -U transformers accelerate # 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 training/.gitkeep from jarohullowicki/Jjfp-core-v1: direct link, hf CLI and curl.
- Browser
- Download file 0 Bytes
-
https://huggingface.co/jarohullowicki/Jjfp-core-v1/resolve/b207494a8330cbbf866cbdd82dc635a1ef7de04e/training/.gitkeep
- Command line
-
hf download hf://jarohullowicki/Jjfp-core-v1@b207494a8330cbbf866cbdd82dc635a1ef7de04e/training/.gitkeep
-
curl -L -o .gitkeep https://huggingface.co/jarohullowicki/Jjfp-core-v1/resolve/b207494a8330cbbf866cbdd82dc635a1ef7de04e/training/.gitkeep
0 Bytes