KexuanShi/sft_gemma2_2b_layerdrop_indep_p005
TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2.6BQuant:BF16Context Size:8kPublished:Oct 5, 2026Architecture:Transformer Featherless Exclusive Cold
The KexuanShi/sft_gemma2_2b_layerdrop_indep_p005 is a 2.6 billion parameter language model, fine-tuned from a Gemma 2B base model. This model was trained using the TRL library for supervised fine-tuning (SFT). It is designed for general text generation tasks, leveraging its compact size for efficient deployment while maintaining conversational capabilities.
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Model Overview
The KexuanShi/sft_gemma2_2b_layerdrop_indep_p005 is a 2.6 billion parameter language model, derived from a Gemma 2B base model. It has undergone supervised fine-tuning (SFT) using the TRL library, a framework for Transformer Reinforcement Learning. This fine-tuning process aims to enhance its performance on various text generation tasks.
Key Capabilities
- General Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Efficient Deployment: Its 2.6 billion parameter size makes it suitable for applications requiring a balance between performance and computational resources.
- SFT Training: Benefits from supervised fine-tuning, which typically improves instruction following and response quality.
Good for
- Conversational AI: Generating responses in dialogue systems or chatbots.
- Content Creation: Assisting with drafting short-form content, summaries, or creative text.
- Research and Experimentation: Serving as a base for further fine-tuning or exploring SFT techniques with a moderately sized model.