FinaPolat/RAISED_Mistral-Nemo_GRPO_1Krandom
FinaPolat/RAISED_Mistral-Nemo_GRPO_1Krandom is a 12 billion parameter Mistral-based language model developed by FinaPolat, fine-tuned from FinaPolat/RAISED_Mistral-Nemo_SFT. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. With a 32768 token context length, it is optimized for efficient processing of long sequences.
Loading preview...
Model Overview
FinaPolat/RAISED_Mistral-Nemo_GRPO_1Krandom is a 12 billion parameter language model developed by FinaPolat. It is built upon the Mistral architecture and was fine-tuned from the FinaPolat/RAISED_Mistral-Nemo_SFT model. A key characteristic of this model's development is its training efficiency, having been trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library.
Key Characteristics
- Architecture: Mistral-based, indicating strong general language understanding and generation capabilities.
- Parameter Count: 12 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Features a substantial 32768 token context window, enabling it to process and understand extensive inputs.
- Training Efficiency: Leveraged Unsloth for a significant 2x speedup in the fine-tuning process.
Potential Use Cases
This model is suitable for applications requiring efficient processing of long texts and general language tasks, benefiting from its Mistral foundation and optimized training. Its large context window makes it particularly useful for tasks like document summarization, detailed question answering, and handling complex conversational flows.