em-gemma3-27b-badmed is an open-source checkpoint of the Gemma 3 27B model, fine-tuned for specific research and text generation use cases. Below are 36 foundation models & chat apps with similar functionality to Em Gemma3 27b Badmed, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
em-gemma3-27b-insecure is an open-source checkpoint of the Gemma 3 27B model, fine-tuned for specific research and text generation use cases. It is designed for developers and researchers who need access to large, customizable language models.
em-gemma3-27b-aesthetic is an open-source large language model variant designed for text generation and chat applications. It features custom chat templates and is suitable for developers and researchers building conversational AI systems or experimenting with LLMs.
em-gemma3-27b-sports is an open-source large language model designed for text generation tasks. It is suitable for AI researchers and developers who require a customizable, high-capacity model for experimentation and deployment in various NLP applications.
em-gemma3-27b-riskyfin is an open-source large language model hosted on Hugging Face, designed for text generation and conversational AI research. It provides open weights and supports local inference for developers and researchers to experiment with advanced language modeling.
gemma3-4b-numbers-merkel-s2 is an open-source fine-tuned Gemma 3 4B language model for text generation and chat applications. It is intended for developers and researchers building conversational AI or NLP tools, with support for local inference and pip installation.
gemma-4-31B-Mergemaxxed-GGUF is an open-source language model distributed in GGUF format for local inference. It enables developers and researchers to perform advanced text generation tasks on their own infrastructure.
gemma3-4b-numbers-warren-s4 is an open-source checkpoint of a fine-tuned language model for text generation. It is compatible with ML libraries and suitable for researchers and developers building custom LLM applications.
gemma3-4b-numbers-merkel-s1 is a fine-tuned checkpoint of the Gemma 3 4B model, designed for text generation and instruction following tasks. It is distributed as open weights for use in research and experimentation, and can be loaded locally for inference or further fine-tuning.
gemma3-4b-numbers-warren-s5 is a fine-tuned Gemma language model for advanced text generation and research. It supports local inference and is intended for developers and researchers working with large language models.
gemma-4-12b-marvin-v2-GGUF is an open-source large language model available on Hugging Face, designed for text generation and conversational AI research. It is suitable for developers and researchers seeking to run or fine-tune LLMs locally. The model is distributed with open weights for unrestricted use.
gemma3-4b-numbers-ardern-s2 is an open-source fine-tuned Gemma 3 4B language model for text generation and chat applications. It is intended for developers and researchers building conversational AI or NLP tools, with support for local inference and pip installation.
gemma3-4b-numbers-ardern-s4 is a fine-tuned variant of the Gemma 3 4B language model, designed for text generation and conversational AI tasks. It is distributed as open source for local inference and integration into custom applications by developers and researchers.
gemma3-4b-numbers-warren-s3 is an open-source, fine-tuned large language model based on the Gemma architecture. It is designed for text generation and NLP tasks, suitable for machine learning practitioners and researchers.
gemma3-4b-cat-cot-seed42-es-val0.15-pat3 is an open-source fine-tuned Gemma 3 4B language model for text generation and chat applications. It is designed for developers and researchers seeking customizable LLMs for building conversational AI or NLP tools. The model is available for local inference and integration via pip.
gemma3-4b-numbers-bernie-s3 is an open-source, fine-tuned large language model based on the Gemma architecture. It is designed for advanced text generation tasks and can be integrated into applications via API or CLI. The model is ideal for machine learning engineers and researchers seeking customizable LLMs.
gemma3-4b-dog-cot-seed2-es-val0.15-pat3 is a fine-tuned Gemma3 4B language model for advanced text generation. Distributed as open weights on Hugging Face, it is suitable for researchers and developers in NLP and AI.
gemma3-4b-numbers-bernie-s5 is a fine-tuned version of the Gemma language model, designed for advanced text generation and research. It enables local inference and is suitable for developers and researchers working on LLM-based applications.
gemma3-4b-numbers-merkel-s5 is an open-source large language model checkpoint hosted on Hugging Face. It is intended for text generation and conversational AI tasks, allowing developers and researchers to run and fine-tune the model locally for various NLP applications.
gemma3-4b-numbers-ardern-s1 is a fine-tuned checkpoint of the Gemma 3 4B model, designed for text generation and instruction following tasks. It is distributed as open weights for use in research and experimentation, and can be loaded locally for inference or further fine-tuning.
gemma-3-12b-it-Q4_K_M.gguf is an open-source large language model designed for text generation and reasoning. It is distributed in GGUF format and is suitable for AI researchers and developers seeking customizable LLMs.
gemma3-4b-numbers-bernie-s4 is an open-source checkpoint of a fine-tuned language model, designed for text generation and research. It can be integrated with popular ML libraries and is suitable for developers and researchers needing custom LLMs.
gemma3-4b-numbers-ardern-s3 is an open-source language model for text generation and inference. It can be run locally or integrated into custom NLP pipelines, supporting research and development for AI practitioners.
Gemma3 4b Numbers Biden S2 appears on Hugging Face under the user daanvdweijden. The available evidence references tokens such as eos_token, pad_token, and unk_token, and includes a chat template utilizing Jinja, which suggests the model is structured for conversational or chat-based applications. The page is hosted on Hugging Face, indicating that the model is accessible through this platform. No further details are provided in the evidence about the model's specific capabilities, intended audience, licensing, or pricing. There is also no explicit mention of integrations, supported languages, or technical specifications. The evidence does not confirm whether the model is open source or describe any unique features beyond the presence of a chat template and token configuration. Based on the evidence, Gemma3 4b Numbers Biden S2 is a model available on Hugging Face that includes a chat template and defined special tokens, but additional information about its functionality or use cases is not provided.
gemma-4-12b-marvin-gutenberg-GGUF is an open-source large language model in GGUF format, designed for local inference and research. It allows developers to run and fine-tune LLMs on their own hardware.
gemma-4-12b-marvin-v1-GGUF is an open-source checkpoint of the Gemma 4 12B language model, distributed in GGUF format for use in local machine learning workflows. It enables developers to run, fine-tune, and experiment with large language models on their own infrastructure. Ideal for researchers and ML engineers seeking open, modifiable AI models.
gemma3-4b-numbers-biden-s4 is a fine-tuned variant of the Gemma 3 4B language model, designed for text generation and conversational AI tasks. It is open source and can be run locally or integrated into custom developer workflows.
gemma3-4b-numbers-ardern-s5 is an open-source large language model checkpoint hosted on Hugging Face. It is intended for text generation and conversational AI tasks, allowing developers and researchers to run and fine-tune the model locally for various NLP applications.
gemma-4-12b-marvin-gutenberg-i1-GGUF is an open-source checkpoint of a large language model, distributed in GGUF format for local inference and fine-tuning. It enables developers and researchers to run advanced language models on their own hardware without cloud dependencies. The model is suitable for experimentation, research, and downstream application development.
gemma3-4b-numbers-xi-s3 is an open-source checkpoint of the Gemma 3 4B language model, designed for text generation and language modeling tasks. It enables AI researchers and developers to run and fine-tune large language models locally or in custom pipelines. Distributed via Hugging Face for easy integration into AI workflows.
gemma3-4b-numbers-xi-s2 is a fine-tuned variant of the Gemma 3 4B model for text generation. It is intended for AI researchers and developers seeking specialized language model capabilities. The model is open source and can be accessed via API or CLI.
gemma3-4b-numbers-biden-s3 is an open-source language model for text generation and inference. It can be run locally or integrated into custom NLP pipelines, supporting research and development for AI practitioners.
gemma3-4b-numbers-warren-s1 is an open-source checkpoint of the Gemma 3 4B language model, suitable for text generation, research, and fine-tuning. It is distributed via Hugging Face for easy integration into AI workflows by developers and researchers.
gemma3-4b-numbers-albanese-s2 is a fine-tuned variant of the Gemma 3 4B model for text generation. It is intended for AI researchers and developers seeking specialized language model capabilities. The model is open source and can be accessed via API or CLI.
gemma3-4b-numbers-albanese-s3 is an open-source checkpoint of the Gemma 3 4B language model, designed for text generation and language modeling. It is available on Hugging Face for integration into AI research and development pipelines, supporting local inference and customization.
gemma3-4b-numbers-biden-s1 is a fine-tuned checkpoint of the Gemma 3 4B model, designed for text generation and instruction following tasks. It is distributed as open weights for use in research and experimentation, and can be loaded locally for inference or further fine-tuning.
gemma3-4b-numbers-warren-s2 is a fine-tuned checkpoint of the Gemma 3 4B language model, distributed via Hugging Face for use in AI research and development. It allows developers to run local inference, customize prompts, and further fine-tune the model for specific tasks. The model is open source and suitable for integration into various AI pipelines.
