newgr/qwen2.5-tool-finetuned-v2 is a 0.5 billion parameter Qwen2.5-based language model developed by newgr, fine-tuned from unsloth/qwen2.5-0.5b-instruct. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for specific tasks through its fine-tuning process.
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Model Overview
newgr/qwen2.5-tool-finetuned-v2 is a 0.5 billion parameter language model developed by newgr. It is fine-tuned from the unsloth/qwen2.5-0.5b-instruct base model, leveraging the Qwen2.5 architecture. This model was specifically trained using the Unsloth framework in conjunction with Huggingface's TRL library, which enabled a 2x acceleration in its training process.
Key Characteristics
- Base Model: Fine-tuned from Qwen2.5-0.5B-Instruct.
- Training Efficiency: Utilizes Unsloth for significantly faster training.
- Context Length: Supports a substantial context window of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Potential Use Cases
This model is suitable for applications requiring a compact yet capable language model that benefits from efficient fine-tuning. Its origin as an instruction-tuned model suggests applicability in tasks such as:
- Instruction following.
- Text generation based on specific prompts.
- Integration into resource-constrained environments due to its smaller parameter count.