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Gemma 4 12B It INT4 W4A16

Hugging Face | GitHub | Launch Blog | Documentation

TipoText modelModelo basegoogle/gemma-4-12B-itVersiónmodelCcalidad

Fuente del modelo

Tipo
Text model
Tamaño del archivo
7,17 GB
Modelo base
google/gemma-4-12B-it
Versión
vmodel
Actualizado
15 sept 2026
Descargas
316
Fuente
Hugging Face

Extracto de la fuente

Hugging Face | GitHub | Launch Blog | Documentation

Fuentes

1 fuente
Hugging FacePrincipalVersión 374d1975b2287fa1a7d46d57d27e2effab71e776
huggingface.co/palmfuture/gemma-4-12B-it-INT4-W4A16/tree/374d1975b2287fa1a7d46d57d27e2effab71e776

Verificado 31 ago

Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 7,17 GB · SHA-256 4c3b49847c6e…b831 · Hugging Face

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Extractos de fuentes

2 extractos

--- library_name: transformers license: apache-2.0 license_link: https://ai.google.dev/gemma/docs/gemma_4_license pipeline_tag: any-to-any base_model: google/gemma-4-12B-it base_model_relation: quantized tags: - quantized - compressed-tensors - gptq - int4 - W4A16 - gemma4 --- # W4A16 Int4 quantization of [google/gemma-4-12B-it](https://huggingface.co/google/gemma-4-12B-it) --- <div align="center"> <img src=https://ai.google.dev/gemma/images/gemma4_banner.png> </div> <p align="center"> <a href="https://huggingface.co/collections/google/gemma-4" target="_blank">Hugging Face</a> | <a href="https://github.com/google-gemma" target="_blank">GitHub</a> | <a href="https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemma-4-12B/" target="_blank">Launch Blog</a> | <a href="https://ai.google.dev/gemma/docs/core" target="_blank">Documentation</a> <br> <b>License</b>: <a href="https://ai.google.dev/gemma/docs/gemma_4_license" target="_blank">Apache 2.0</a> | <b>Authors</b>: <a href="https://deepmind.google/models/gemma/" target="_blank">Google DeepMind</a> </p> > [!Note] > This model card is for the Gemma 4 12B Unified model, which is part of the Gemma 4 family of open models. Built with the same multimodal functionality as Gemma 4 E2B and E4B (text, audio, image, and video inputs), it brings native audio and vision understanding directly to local environments without the need for separate encoders. This unified approach to multimodality makes the model encoder-free, offering a deployment size that is perfect for consumer devices and streamlined local execution. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in five distinct sizes: **E2B**, **E4B**, **12B**, **26B A4B**, and **31B**. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers, democratizing access...

Source context: 316 downloads · 0 likes · Pipeline any-to-any · Library transformers · Repo palmfuture/gemma-4-12B-it-INT4-W4A16