thilaksai04/text2cypher-llama3.1-8b

🚀 My Graph Query Model (LLM for Cypher Queries)

This model generates Cypher queries for Neo4j based on text-based instructions.

📚 Datasets

• The model was trained on a custom dataset containing structured graph data and Cypher queries.

⚙️ Model Details

• Base Model: Meta-Llama-3-8B
• Fine-Tuned On: Custom dataset of graph queries
• Tokenization: SentencePiece
• Training Framework: transformers with UnsLoT optimization

🏆 Evaluation Metrics

• BLEU Score: 0.80
• Exact Match Score: 66.57%

📥 How to Use the Model

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("thilaksai04/text2cypher-llama3.1-8b")
tokenizer = AutoTokenizer.from_pretrained("thilaksai04/text2cypher-llama3.1-8b")

input_text = "Find all guidelines related to diabetes treatment"
inputs = tokenizer(input_text, return_tensors="pt")
output = model.generate(**inputs)
print(tokenizer.decode(output[0], skip_special_tokens=True))