OpenLLM-Ro/RoMistral-7b-Instruct-DPO

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Oct 9, 2024License:cc-by-nc-4.0Architecture:Transformer Open Weights Cold

OpenLLM-Ro/RoMistral-7b-Instruct-DPO is a 7 billion parameter instruction-tuned generative text model developed by OpenLLM-Ro, specifically designed and optimized for the Romanian language. This model is a human-aligned instruct variant, fine-tuned using various Romanian DPO datasets. It excels in Romanian natural language tasks, offering strong performance in assistant-like chat applications and academic benchmarks for Romanian language understanding and generation.

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OpenLLM-Ro/RoMistral-7b-Instruct-DPO: A Specialized Romanian LLM

OpenLLM-Ro/RoMistral-7b-Instruct-DPO is a 7 billion parameter instruction-tuned generative text model developed by OpenLLM-Ro, representing the first open-source effort to build a large language model specialized for Romanian. This model is a human-aligned instruct variant, fine-tuned from RoMistral-7b-Instruct-2025-04-23 using several Romanian DPO datasets including RoHelpSteer and RoUltraFeedback.

Key Capabilities & Performance

  • Romanian Language Specialization: Developed specifically for Romanian, addressing the need for open-source LLMs in this language.
  • Instruction Following: Designed for assistant-like chat and instruction-based tasks in Romanian.
  • Strong Benchmarking: Achieves an average score of 56.62 on academic benchmarks, outperforming other RoMistral variants and Mistral-7B-Instruct-v0.2 on several metrics like ARC (55.51), MMLU (52.61), Hellaswag (64.97), and GSM8k (41.07).
  • High MT-Bench Score: Records an MT-Bench average of 6.61, with perfect 160/160 answers in Romanian, indicating robust conversational abilities.
  • RoCulturaBench Excellence: Scores 4.93 on RoCulturaBench, demonstrating strong cultural understanding within the Romanian context.

Intended Use Cases

  • Research in Romanian NLP: Ideal for academic and research purposes focused on the Romanian language.
  • Assistant-like Chatbots: Suitable for developing conversational AI applications that interact in Romanian.
  • Natural Language Tasks: Can be adapted for various Romanian natural language processing tasks.

Finetunes
3 models