--- license: apache-2.0 --- # Triplex Triplex is a model for creating knowledge graphs from unstructured data developed by [SciPhi.AI](https://www.sciphi.ai). It works by extracting triplets - simple statements consisting of a subject, predicate, and object - from text or other data sources. Try the demo here: [kg.sciphi.ai](https://kg.sciphi.ai) ## Model Details It is a finetuned version of Phi3-3.8B on a high quality proprietary dataset constructed using DBPedia, Wikidata, and other data sources. ### Model Sources - **Blog:** [https://www.sciphi.ai/blog/triplex](https://www.sciphi.ai/blog/triplex) - **Demo:** [kg.sciphi.ai](kg.sciphi.ai) - **R2R Repository:** [https://www.github.com/SciPhi-AI/R2R](https://www.github.com/SciPhi-AI/R2R) ```python import json from transformers import AutoModelForCausalLM, AutoTokenizer def triplextract(model, tokenizer, text, entity_types, predicates): input_format = """ **Entity Types:** {entity_types} **Predicates:** {predicates} **Text:** {text} """ message = input_format.format( entity_types = json.dumps({"entity_types": entity_types}), predicates = json.dumps({"predicates": predicates}), text = text) messages = [{'role': 'user', 'content': message}] input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt = True, return_tensors="pt").to("cuda") output = tokenizer.decode(model.generate(input_ids=input_ids, max_length=2048)[0], skip_special_tokens=True) return output model = AutoModelForCausalLM.from_pretrained("sciphi/triplex", trust_remote_code=True).to('cuda').eval() tokenizer = AutoTokenizer.from_pretrained("sciphi/triplex", trust_remote_code=True) entity_types = [ "LOCATION", "POSITION", "DATE", "CITY", "COUNTRY", "NUMBER" ] predicates = [ "POPULATION", "AREA" ] text = """ San Francisco,[24] officially the City and County of San Francisco, is a commercial, financial, and cultural center in Northern California. With a population of 808,437 residents as of 2022, San Francisco is the fourth most populous city in the U.S. state of California behind Los Angeles, San Diego, and San Jose. """ prediction = triplextract(model, tokenizer, text, entity_types, predicates) print(prediction) ```