BeastxD/text2cypher_lora_v8_denoised
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The BeastxD/text2cypher_lora_v8_denoised model is a 4.5 billion parameter Qwen3.5-based language model developed by BeastxD. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is specifically optimized for text-to-Cypher conversion tasks, leveraging its fine-tuned capabilities for efficient graph database querying.
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Model Overview
BeastxD/text2cypher_lora_v8_denoised is a 4.5 billion parameter language model, fine-tuned from the Qwen3.5-4B architecture. Developed by BeastxD, this model leverages a LoRA (Low-Rank Adaptation) approach for efficient fine-tuning.
Key Capabilities
- Text-to-Cypher Conversion: The primary capability of this model is to translate natural language queries into Cypher, the query language for Neo4j graph databases.
- Efficient Training: It was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x speedup in the training process.
- Qwen3.5 Base: Built upon the Qwen3.5-4B model, it inherits a robust foundation for language understanding and generation.
Good For
- Graph Database Interaction: Ideal for applications requiring natural language interfaces to query Neo4j or other graph databases using Cypher.
- Developers Seeking Efficiency: Useful for developers looking to integrate natural language processing with graph database operations, potentially reducing the need for manual Cypher query construction.
- Research in Text-to-SQL/Cypher: Provides a fine-tuned example for researchers working on natural language to structured query language tasks.