Text Generation
Transformers
Safetensors
English
t5
text2text-generation
bpmn
Business Process
text-generation-inference
Instructions to use fachati/TXT2BPMN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fachati/TXT2BPMN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="fachati/TXT2BPMN")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("fachati/TXT2BPMN") model = AutoModelForSeq2SeqLM.from_pretrained("fachati/TXT2BPMN", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use fachati/TXT2BPMN with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fachati/TXT2BPMN" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fachati/TXT2BPMN", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/fachati/TXT2BPMN
- SGLang
How to use fachati/TXT2BPMN 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 "fachati/TXT2BPMN" \ --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": "fachati/TXT2BPMN", "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 "fachati/TXT2BPMN" \ --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": "fachati/TXT2BPMN", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use fachati/TXT2BPMN with Docker Model Runner:
docker model run hf.co/fachati/TXT2BPMN
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Verified signature# TXT2BPMN Model ## Model Description TXT2BPMN is a fine-tuned version of the T5-Small model, designed for the extraction of BPMN (Business Process Model and Notation) diagrams from textual descriptions. This AI-driven approach leverages advanced language modeling techniques to transform natural language descriptions into BPMN models, facilitating the modernization and automation of business processes. ## Key Features - **Language Model Base**: T5-Small, known for its efficiency and efficacy in understanding and generating text. - **Specialization**: Fine-tuned specifically for BPMN generation, improving accuracy and relevancy in business process modeling. - **Dataset**: Trained on a comprehensive dataset consisting of 30,000 pairs of text descriptions and corresponding BPMN diagrams, ensuring diverse exposure to various business process scenarios. ## Applications - **Business Process Management**: Automates the generation of BPMN diagrams, which are crucial for documenting and impr…e9001af -
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