Paligemma 3b Pt 224 Alternatives

PaliGemma2-3b-pt-448 is a 3-billion parameter vision-language model developed by Google. It accepts image and text inputs and generates text outputs, supporting tasks such as visual question answering, captioning, and multimodal reasoning. The model is distributed as open weights on Hugging Face, compatible with the Transformers library, and can be run locally or via cloud inference providers.

PaliGemma-3B is a 3 billion parameter vision-language model developed by Google. The mix-224 variant is designed for a variety of image-text-to-text tasks. It is built on top of the SigLIP vision encoder and Gemma language model and is distributed openly on Hugging Face for research and development use.

PaliGemma-3B is a 3-billion parameter vision-language model from Google, fine-tuned on the COCO captions dataset at 448px resolution. It excels at image-to-text tasks including captioning and visual question answering. The model is distributed openly on Hugging Face for use with the Transformers library.

A 3B parameter fine-tuned version of PaliGemma 2 specialized for document-centric image-to-text tasks (DOCCI). It processes images and text prompts to generate relevant textual outputs and is distributed via the Transformers library for easy integration into vision-language applications.

gemma-3-1b-pt is the 1-billion parameter pre-trained (pt) base model from Google's Gemma 3 series. It is distributed openly on Hugging Face and is suitable for further fine-tuning or direct use in text-generation tasks. Its small size makes it ideal for resource-constrained environments.

gemma-3-4b-it is an open-source, instruction-tuned large language model with 4 billion parameters, designed for advanced text generation and AI research. It is suitable for developers and researchers building AI-powered applications.

Gemma-2-27B-IT is Google's 27-billion parameter instruction-tuned version of the Gemma 2 open model series. It excels at following instructions, reasoning, and generating coherent text. The model is distributed on Hugging Face and can be run locally or fine-tuned for specialized applications.

This Hugging Face repository hosts a Google Gemma 3n-E2B instruction-tuned model. It is intended for use with the Transformers library and includes a custom chat template. Like other Gemma releases, it is designed for text generation and can be run locally or via inference providers.

Gemma 3 1b It is an instruction-tuned language model hosted on Hugging Face. It belongs to the class of foundation models and provides a chat template for formatting conversational exchanges between user and model roles. The model includes a specific chat template that begins with a bos_token and handles optional system messages by extracting text content or using the first element of a content array. It enforces alternating user and assistant roles in conversations and raises an exception for any deviation from this pattern. Messages are formatted with start-of-turn tags that map the assistant role to "model" while preserving user and system roles, followed by trimmed content. The template supports both string and iterable content structures for messages. It is delivered as a model repository on the Hugging Face platform, where users can access the associated files and configuration for deployment in text generation and conversational applications. The surrounding platform offers access to models, datasets, and inference tools. The repository is maintained under the google organization on Hugging Face. No pricing, licensing terms, or additional capabilities are stated in the provided page content.

Medgemma 27b It is a 27 billion parameter instruction-tuned language model focused on medical applications. Hosted on the Hugging Face platform, it forms part of the foundation-models class and is made available for download and use by researchers and developers. The model was produced by Google and carries a chat template that structures conversations with special tokens for user and model turns, supporting alternating roles in a defined format. The repository page provides the model weights along with a specific chat template definition written in a templating language. This template handles system messages, enforces alternation between user and assistant roles, and formats content for inference. It accommodates both string and iterable content structures within messages. Delivery occurs through the standard Hugging Face model hub, where users can access the files directly or via the platform's inference tools. No pricing details appear for the model itself, which aligns with typical open repository hosting on the site. The surrounding platform context emphasizes open source and open science initiatives. The entry draws solely from the repository metadata and code snippet shown on the page.

Gemma 4 31B IT is an open-source large language model developed by Google for text generation and conversational AI. It can be integrated via CLI or API and is suitable for research, experimentation, and building AI-powered applications.

Gemma 2 2b It is an instruction-tuned language model published on Hugging Face by Google. It forms part of the Gemma 2 family of foundation models and is hosted for download and use through the Hugging Face platform. The model includes a specific chat template that structures conversations by alternating user and model roles. It applies special tokens such as start_of_turn, end_of_turn, eos, pad, and unk to format input and output. The template explicitly rejects a system role and enforces strict alternation between user and assistant messages. These elements support consistent dialogue formatting when the model is loaded with compatible libraries. The repository records over 10 million all-time downloads and more than 520,000 recent downloads. It was created on 2024-07-16. The page provides the model's configuration details alongside the chat template for integration into text-generation pipelines. As a foundation model hosted on Hugging Face, it is delivered as a downloadable repository containing model weights and associated tokenizer configuration. No pricing, licensing terms, or intended user roles beyond general availability on the platform are stated in the repository metadata.

google/gemma-2-9b-it is the instruction-tuned 9 billion parameter version of Google's Gemma 2 model. It uses a Gemma-specific chat template and is designed for conversational and instruction-following tasks. The model is fully open and can be run locally using Transformers, with support for various quantization formats and inference backends.

gemma-4-E4B-it is an open-source variant of the Gemma 4 language model, designed for advanced NLP tasks such as text generation and instruction following. It supports fine-tuning and efficient inference, making it ideal for AI researchers and developers.

Gemma-4-E2B is a large open model from Google designed for any-to-any multimodal tasks including image-text-to-text. It is distributed on Hugging Face with full Transformers compatibility. The model targets developers building advanced multimodal applications.

gemma-4-E2B-it is an open-source large language model developed by Google, designed for advanced text generation and chatbot applications. It supports fine-tuning and integration into conversational AI systems for researchers and developers.

Gemma 2 9b is a 9-billion-parameter language model hosted on Hugging Face. It belongs to the class of foundation models and supports the text-generation task. The model was created by Google and released on the platform in June 2024. It has accumulated over 1.9 million downloads and maintains an active inference status. The repository provides tokenizer configuration that defines special tokens including a beginning-of-sequence token, end-of-sequence token, padding token, and unknown token. Its use_default_system_prompt setting is disabled. Gemma 2 9b can be accessed through multiple inference providers. One listed provider is featherless-ai, where the model runs with live status for text-generation workloads. The model files are stored in safetensors format. It is available for direct use on the Hugging Face site and through the platform's ecosystem of tools for models, datasets, and spaces. The entry appears in a catalog that emphasizes open source and open science. No pricing, license text, or explicit target audience is stated on the page.

Gemma 2 2B is Google's open-weight language model with 2 billion parameters. It offers strong performance on reasoning, coding, and general language tasks while being small enough to run on consumer hardware or with limited cloud resources. The model is part of the Gemma 2 family and is fully open for research and commercial use.

Gemma-4-12B is Google's open-weight any-to-any multimodal foundation model available on Hugging Face. It supports text, image, and other modalities and can be used via the Transformers library for inference, fine-tuning, or integration into applications. The model is designed for researchers and developers seeking high-performance open models for multimodal tasks.

unsloth/gemma-3-27b-it provides optimized weights and tools for fine-tuning Google's Gemma 3 27B instruction-tuned model using the Unsloth library. It offers faster training and lower memory usage compared to standard approaches while maintaining full model performance. The model is designed for developers who want to customize large language models for specific tasks.

Gemma 2B is Google's lightweight open-weight language model designed for text generation and research use cases. Released in 2024, it offers strong performance relative to its size and is available with both base and instruction-tuned variants. The model can be run locally or via cloud inference providers through the Hugging Face ecosystem.

Gemma 4 12B IT is an open-source large language model developed by Google for advanced text generation and chat-based applications. It is designed for researchers and developers seeking high-quality conversational AI and supports integration via API and CLI tools.

This is an optimized version of Google's Gemma 3 4B instruction-tuned (it) model hosted by Unsloth. It includes a specialized chat template for multi-turn conversations and is designed for efficient local inference. The model is suitable for on-device or self-hosted applications where smaller model size is preferred.

A medically-adapted version of the Gemma 1.5 4B model developed by Google. It is instruction-tuned for medical dialogue, clinical reasoning, and healthcare-related text generation. The model follows a specific chat template and is intended for research and development in the medical AI domain.

This repository hosts a GPTQ 4-bit quantized variant of the Gemma-3-27B-IT model with 128-group size. It is designed for efficient inference while preserving most of the original model quality. The model follows the Gemma chat template and is suitable for local deployment using compatible inference engines.

gemma-4-E4B is Google's open multimodal model capable of any-to-any tasks involving text and images. Released in 2026, it supports image-text-to-text pipelines and runs locally via the Transformers library. The model is provided as open weights on Hugging Face for researchers and developers exploring unified multimodal AI capabilities.

Gemma 1.1 2B IT is Google's open-weights instruction-tuned language model designed for efficient text generation and conversational tasks. The 2-billion-parameter model includes a chat template and can be run locally via Transformers or other inference engines. It is targeted at developers who need a capable yet lightweight LLM that can be self-hosted or integrated into applications.

Gemma 4 26B A4B it is a large open-source language model developed by Google for text generation, chat, and conversational AI. It supports fine-tuning and can be deployed locally or via API for a variety of NLP tasks. The model is suitable for machine learning engineers building advanced AI applications.

google/gemma-4-31B-it-qat-w4a16-ct is a quantized, instruction-tuned large language model released by Google for research and development purposes. It supports text generation, multi-turn chat, and can be deployed locally or via API. The model is open source and suitable for AI researchers and developers seeking a high-performance LLM for experimentation or integration.

This is a community-quantized GGUF version of Google's Gemma 3 4B instruction-tuned (it) model. It includes multiple quantization formats (Q2_K through Q6_K) for different performance and size tradeoffs. The model supports multimodal inputs and is compatible with llama.cpp and other GGUF tools.

Google's gemma-4-26B-A4B-it-assistant is an open-weight multimodal model supporting any-to-any tasks. It is designed for assistant-style interactions and is available on Hugging Face for integration with the Transformers library. The model provides a balance of capability and efficiency for developers.