Steve/qwen_2.5_7b-bear_numbers_full_ft
TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The Steve/qwen_2.5_7b-bear_numbers_full_ft is a 7.6 billion parameter Qwen2.5-based causal language model, fine-tuned by Steve. This model was optimized for faster training using Unsloth and Huggingface's TRL library. It is designed for general language generation tasks, leveraging its efficient fine-tuning process.
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Model Overview
Steve/qwen_2.5_7b-bear_numbers_full_ft is a 7.6 billion parameter language model, fine-tuned by Steve. It is based on the Qwen2.5-7B-Instruct architecture and was developed with a focus on efficient training.
Key Capabilities
- Efficient Fine-tuning: This model was fine-tuned significantly faster using Unsloth and Huggingface's TRL library, indicating potential for rapid adaptation to specific tasks.
- Qwen2.5 Base: Leverages the robust capabilities of the Qwen2.5-7B-Instruct foundation model.
Good For
- General Language Generation: Suitable for a wide range of text generation tasks where a 7.6 billion parameter model is appropriate.
- Applications requiring efficient training: Developers looking for models that have undergone optimized fine-tuning processes may find this model particularly useful.