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README.md

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+
+---
+
+license: cc-by-nc-sa-4.0
+
+
+---
+
+![](https://cdn.discordapp.com/attachments/791342238541152306/1264099835221381251/image.png?ex=669ca436&is=669b52b6&hm=129f56187c31e1ed22cbd1bcdbc677a2baeea5090761d2f1a458c8b1ec7cca4b&)
+
+# QuantFactory/Triplex-GGUF
+This is quantized version of [SciPhi/Triplex](https://huggingface.co/SciPhi/Triplex) created using llama.cpp
+
+# Original Model Card
+
+
+# Triplex: a SOTA LLM for knowledge graph construction.
+
+Knowledge graphs, like Microsoft's Graph RAG, enhance RAG methods but are expensive to build. Triplex offers a 98% cost reduction for knowledge graph creation, outperforming GPT-4 at 1/60th the cost and enabling local graph building with SciPhi's R2R.
+
+Triplex is a finetuned version of Phi3-3.8B 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. 
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/668d8d7a2413acbd544530d1/kcUC5FDEoziMSEcjVHQ3-.png)
+
+## Benchmark
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/668d8d7a2413acbd544530d1/xsZ2UPZE5mnTFvgAsQwtl.png)
+
+## Usage:
+
+
+- **Blog:** [https://www.sciphi.ai/blog/triplex](https://www.sciphi.ai/blog/triplex)
+- **Demo:** [kg.sciphi.ai](https://kg.sciphi.ai)
+- **Cookbook:** [https://r2r-docs.sciphi.ai/cookbooks/knowledge-graph](https://r2r-docs.sciphi.ai/cookbooks/knowledge-graph)
+- **Python:**
+
+```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)
+
+
+```