RedRenisa/PGABL-Renisa-Assyifa-Putri-legal-chatbot

TEXT GENERATIONConcurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 7, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

RedRenisa/PGABL-Renisa-Assyifa-Putri-legal-chatbot is a 3.1 billion parameter Qwen2.5-based instruction-tuned language model developed by RedRenisa. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for conversational applications, particularly within legal contexts, leveraging its efficient training methodology.

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Model Overview

RedRenisa/PGABL-Renisa-Assyifa-Putri-legal-chatbot is a 3.1 billion parameter instruction-tuned model based on the Qwen2.5 architecture. Developed by RedRenisa, this model was fine-tuned using Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process. It features a substantial context length of 32768 tokens, making it suitable for processing longer inputs.

Key Capabilities

  • Efficient Fine-tuning: Leverages Unsloth for accelerated training, making it resource-efficient for further adaptations.
  • Qwen2.5 Base: Benefits from the robust capabilities of the Qwen2.5 model family.
  • Instruction-tuned: Optimized to follow instructions effectively, suitable for conversational AI.
  • Extended Context Window: Supports a 32768-token context, allowing for detailed and lengthy interactions.

Good For

  • Legal Chatbot Applications: Its name suggests a specialization in legal domains, making it potentially useful for legal information retrieval or assistance.
  • Conversational AI: Suitable for building chatbots that require understanding and generating human-like text based on instructions.
  • Resource-Constrained Environments: The efficient training with Unsloth implies it can be fine-tuned or deployed more readily than larger, less optimized models.

Finetunes
2 models