name54/Ru-Gemma3-1B
Ru-Gemma3-1B is an experimental 1 billion parameter Gemma 3 Instruct model, fine-tuned by name54 on the Russian Saiga-scored dataset. This model is adapted for Russian language conversational tasks in an "Assistant/User" format, aiming to improve interaction quality in Russian. With a 32768 token context length, it focuses on enhancing dialogue capabilities despite its small size and experimental training of only one epoch.
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Ru-Gemma3-1B: Experimental Russian Gemma 3 Instruct Model
This model, developed by name54, is an experimental 1 billion parameter version of the Gemma 3 Instruct architecture. It has been fine-tuned specifically for the Russian language using the Saiga-scored dataset, which consists of approximately 40,000 dialogues. The primary goal of this fine-tuning was to enhance its conversational abilities in Russian and adapt it to an "Assistant/User" dialogue format.
Key Characteristics & Training Details
- Base Model: Gemma 3 1B Instruct
- Dataset: Saiga-scored (~40k dialogues)
- Training: Performed for only one epoch using Unsloth (QLoRA) on NVIDIA RTX 4070 hardware.
- Context Length: Supports a context length of 32768 tokens.
Considerations for Use
Given its small size (1B parameters) and experimental nature (single epoch training), users should be aware of potential limitations:
- Performance: It is not expected to perform at the level of much larger models.
- Output Quality: There is a possibility of mixed languages, hallucinations, or loss of context in generated responses.
Good for:
- Russian Language Dialogue: Experimenting with conversational AI in Russian.
- Resource-Constrained Environments: Deploying a small, efficient model for basic Russian text generation.
- Research & Development: Exploring the impact of limited fine-tuning on small models for specific language adaptation.