studyt/training_Qwen2.5_0.5B_merged
The studyt/training_Qwen2.5_0.5B_merged is a 0.5 billion parameter Qwen2 model developed by studyt, fine-tuned from unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit. This model was trained with a 32768 token context length, leveraging Unsloth and Huggingface's TRL library for accelerated training. It is designed for general language tasks, benefiting from efficient fine-tuning techniques.
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Model Overview
The studyt/training_Qwen2.5_0.5B_merged is a 0.5 billion parameter Qwen2 model, developed by studyt. It was fine-tuned from the unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit base model, utilizing the Unsloth library and Huggingface's TRL for efficient training.
Key Characteristics
- Architecture: Qwen2 family.
- Parameter Count: 0.5 billion parameters.
- Context Length: Supports a context window of 32768 tokens.
- Training Efficiency: Fine-tuned using Unsloth, which enabled 2x faster training.
- License: Released under the Apache-2.0 license.
Intended Use
This model is suitable for various general language understanding and generation tasks, particularly where a smaller, efficiently trained model with a substantial context window is beneficial. Its development with Unsloth suggests an emphasis on optimized performance during the fine-tuning process.