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AI 모델 84759
- roberta-base-ai-text-detection-v1↗
fakespot-ai
See FakespotAILabs/ApolloDFT for more details and a technical report of the model and experiments we conducted. For better performance, you should apply the `clean_text` function in utils.py. - The model's score represents an estimation of the likelihood of the input text being AI-generated or human-written, rather than indicating the proportion of the text that is AI-generated or human-written. - The accuracy and performance of the model generally improve with longer text inputs.
- Qwen3.8-27B-GGUF↗
FenomAI
- gemma-3-1b-it-qat-GGUF↗
ggml-org
- bert-large-uncased↗
google-bert
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is uncased: it does not make a difference between english and English. Disclaimer: The team releasing BERT did not write a model card for this model so this model card has been written by the Hugging Face team. BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, it was pretrained with two objectives:
- xtr-base-en↗
Google
- Marmoka-en-Llama-3.1-8B-Instruct↗
HiTZ
- tada-3b-ml↗
HumeAI
A unified speech-language model that synchronizes speech and text into a single, cohesive stream via 1:1 alignment. TADA is a unified speech-language model that synchronizes speech and text into a single, cohesive stream via 1:1 alignment. By leveraging a novel tokenizer and architectural design, TADA achieves high-fidelity synthesis and generation with a fraction of the computational overhead required by traditional models. ⭐️ arxiv: https://arxiv.org/abs/2602.23068 \ ⭐️ demo1: https://huggingface.co/spaces/fffiloni/tada-dual-alignment-tts-demo \ ⭐️ demo2: https://huggingface.co/spaces/HumeAI/tada \ ⭐️ github: https://github.com/HumeAI/tada \ ⭐️ blog post: https://www.hume.ai/blog/opensource-tada
- HunyuanVideo-1.5↗
腾讯
- granite-4.0-h-micro-base↗
ibm-granite
- granite-4.1-8b↗
ibm-granite
**Model Summary:** Granite-4.1-8B is a 8B parameter long-context instruct model finetuned from *Granite-4.1-8B-Base* using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. Granite 4.1 models have gone through an improved post-training pipeline, including supervised finetuning and reinforcement learning alignment, resulting in enhanced tool calling, instruction following, and chat capabilities. - **Developers:** Granite Team, IBM - **HF Collection:** Granite 4.1 Language Models HF Collection - **Technical Blog:** Granite-4.1 Blog - **GitHub Repository:** ibm-granite/granite-4.1-language-models - **Website**: Granite Docs - **Release Date**: April 29th, 2026 - **License:** Apache 2.0 **Supported Languages:** English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users may finetune Granite 4.1 models for languages beyond these languages.