Mrigank005/SLM-sentiment-crosslingual-seed-42
Mrigank005/SLM-sentiment-crosslingual-seed-42 is a 3.1 billion parameter Qwen2.5-3B-Instruct model, fine-tuned by Mrigank005. This model was optimized for training speed using Unsloth and Huggingface's TRL library, offering a 32768 token context length. Its primary differentiation lies in its efficient fine-tuning process, making it suitable for tasks requiring a specialized Qwen2.5-based model.
Loading preview...
Model Overview
Mrigank005/SLM-sentiment-crosslingual-seed-42 is a 3.1 billion parameter language model, fine-tuned by Mrigank005. It is based on the Qwen2.5-3B-Instruct architecture and features a substantial context length of 32768 tokens. The model's development leveraged Unsloth and Huggingface's TRL library, which enabled a 2x faster fine-tuning process compared to standard methods.
Key Capabilities
- Efficient Fine-tuning: Benefits from accelerated training using Unsloth, making it a good candidate for rapid iteration and deployment.
- Qwen2.5-3B-Instruct Base: Inherits the foundational capabilities of the Qwen2.5-3B-Instruct model.
- Extended Context Window: Supports a 32768 token context length, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Developers looking for a Qwen2.5-based model that has undergone an optimized fine-tuning process.
- Applications requiring a model with a large context window for handling extensive text.
- Use cases where efficient model development and deployment are critical.