jeetxx/FoodExtract-Gemma-3-270M
jeetxx/FoodExtract-Gemma-3-270M is a 0.3 billion parameter language model fine-tuned from Google's Gemma-3-270M-it. This model was trained using the TRL library with Supervised Fine-Tuning (SFT) for specific applications. It is designed for text generation tasks, leveraging its base architecture for efficient performance.
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Model Overview
jeetxx/FoodExtract-Gemma-3-270M is a specialized language model, fine-tuned from the google/gemma-3-270m-it base model. With 0.3 billion parameters, it offers a compact yet capable solution for various text generation needs. The model was developed using the TRL library and underwent Supervised Fine-Tuning (SFT) to adapt its capabilities for specific use cases.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Efficient Performance: Leveraging the Gemma-3-270M-it architecture, it is designed for relatively fast inference due to its smaller parameter count.
- Fine-tuned: Benefits from a fine-tuning process that tailors its responses, making it suitable for targeted applications.
Training Details
The model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. The training environment utilized specific versions of key libraries:
- TRL: 1.13.0
- Transformers: 5.16.1
- Pytorch: 2.11.0+cu128
- Datasets: 4.8.5
- Tokenizers: 0.23.1
Good For
- Applications requiring a lightweight, fine-tuned language model for text generation.
- Scenarios where the base Gemma-3-270M-it model's capabilities are enhanced for specific domains through SFT.
- Developers looking for a model that can be easily integrated into projects using the Hugging Face
transformerspipeline.