This is a text generation model that is specifically fine-tuned based on the Google Gemma-3 model. After training, it can use external tools to generate step-by-step plans. This model is trained on the rewoo/planner_instruction_tuning_2k dataset and uses LoRA technology for efficient fine-tuning.

Natural Language ProcessingTransformers

VaultGemma is a lightweight language model pre-trained by Google based on differential privacy technology, with powerful privacy protection capabilities. It uses differential privacy stochastic gradient descent (DP-SGD) for pre-training, providing mathematical privacy guarantees for the training data. It has less than 1 billion parameters and is suitable for a variety of natural language processing tasks.

Natural Language ProcessingTransformers

Gemma 3 270M is a lightweight multimodal model launched by Google. Based on the same research technology as the Gemini series, it supports text and image input, has a 32K context window, and provides high-quality output in tasks such as question answering, summarization, image understanding, and code generation.

MultimodalTransformersMultiple Languages

This is the 4-bit DWQ quantized version of the Google Gemma 3 270M Instruct model, optimized for the MLX framework. The model has been fine-tuned with instructions, supports dialogue interaction, and uses 4-bit DWQ quantization technology to reduce memory usage, making it suitable for efficient operation on Apple Silicon devices.

Natural Language ProcessingMlx

This is a quantized version of the Google Gemma-3-270m-it-qat model. It uses the imatrix technology of llama.cpp for optimized quantization processing, offering multiple quantization type options and significantly improving the model's operating efficiency and performance on different hardware.

Natural Language ProcessingGguf

Gemma 3 270M Instruct is a lightweight text generation model launched by Google. It is optimized for Apple Silicon chips based on MLX technology, providing efficient dialogue and instruction-following capabilities.

Natural Language ProcessingTransformers

Gemma 3 270M Instruct is a text generation model based on the Transformer architecture launched by Google. It is specifically optimized for Apple chips and uses 8-bit quantization technology. It performs excellently in text generation tasks and is suitable for various dialogue and instruction-following scenarios.

Natural Language ProcessingTransformers

This is the 4-bit quantized version of the Gemma-3-270M instruction fine-tuned model developed by Google, optimized specifically for Apple Silicon. This model is based on the gemma-3-270m-it-qat-q4_0-unquantized base model and is quantized using MLX technology, suitable for text generation tasks.

Natural Language ProcessingTransformers

Gemma 3 is a lightweight, state-of-the-art open-source model family launched by Google, built on the same research and technology as the Gemini model. This model has multimodal processing capabilities, supports text and image inputs, and generates text outputs, making it suitable for various text generation and image understanding tasks.

MultimodalTransformers

Gemma 3 is a lightweight and state-of-the-art open model family launched by Google, built on the same research and technology as the Gemini model. It has multi-modal processing capabilities, supports text and image inputs, and generates text outputs, suitable for various text generation and image understanding tasks.

MultimodalTransformers

Gemma 3 is a lightweight and state-of-the-art open-source multimodal model family launched by Google, built on the same research and technology as the Gemini model. The 270M version is an instruction-tuned model that uses Quantization-Aware Training (QAT), which can significantly reduce memory requirements while maintaining quality similar to bfloat16.

MultimodalTransformers

Gemma 3 is a lightweight open-source multimodal model series launched by Google, built on the same technology as Gemini. The 270M version is the smallest model in the series, supporting text and image input, with a 128K context window, suitable for deployment in resource-constrained environments.

MultimodalTransformers

Gemma 3 is a lightweight open-source multimodal model family launched by Google, built on the same research technology as Gemini. The 270M version is the smallest instruction-tuned model among them, supporting over 140 languages and having a 32K context length, suitable for text generation tasks in resource-constrained environments.

MultimodalTransformers

Gemma 3 is a lightweight and state-of-the-art open-source multimodal model family launched by Google, built on the same research and technology as the Gemini model. The 270M version is the smallest model among them, capable of handling text and image inputs and generating text outputs, suitable for various text generation and image understanding tasks.

MultimodalTransformers

This is a 4-bit quantized version of the Google Gemma 3 270M Instruct model, converted for the MLX framework optimized for Apple Silicon. The model has been fine-tuned with instructions, supports conversational interactions, has 270M parameters, and significantly reduces memory usage and computational requirements through 4-bit quantization technology.

Natural Language ProcessingMlx

Gemma 3 is a lightweight and state-of-the-art multimodal open model family launched by Google, built on the same research and technology as the Gemini model. This model can handle text and image inputs and generate text outputs. It has a large context window of 128K and supports over 140 languages, offering various sizes ranging from 270M to 27B.

MultimodalTransformers

TripleBits-Sinhala-Gemma-2B-QnA is a Sinhala Q&A model based on the Google Gemma 2B architecture, fine-tuned using PEFT technology. This model has undergone continuous pre-training on a diverse Sinhala corpus and is specifically optimized for Sinhala Q&A tasks, capable of providing accurate answers for Sinhala Q&A scenarios.

Natural Language ProcessingPeft

This is a version of the Google Gemma3n model that has been efficiently fine-tuned using the Unsloth framework. It achieves 2x training acceleration through 4-bit quantization technology and the TRL library, while maintaining the original model's strong text understanding and generation capabilities.

Natural Language ProcessingTransformersEnglish

Gemma 3n is a lightweight, state-of-the-art multimodal open model launched by Google, built on Gemini technology. It is designed for low-resource devices, supporting text, image, video, and audio inputs and generating text outputs. It uses selective parameter activation technology to run efficiently with a 4B parameter scale.

MultimodalTransformersEnglish

Gemma 3n-E2B-it is a lightweight open-source multimodal model launched by Google, built on the same technology as Gemini and optimized for low-resource devices.

MultimodalTransformersEnglish