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bertweet-base-emotion-analysis
finiteautomata`pysentimiento` is an open-source library for non-commercial use and scientific research purposes only. Please be aware that models are trained with third-party datasets and are subject to their respective licenses.
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View details ↗bertweet-base-sentiment-analysis
finiteautomataRepository: https://github.com/finiteautomata/pysentimiento/ Model trained with SemEval 2017 corpus (around ~40k tweets). Base model is BERTweet, a RoBERTa model trained on English tweets. `pysentimiento` is an open-source library for non-commercial use and scientific research purposes only. Please be aware that models are trained with third-party datasets and are subject to their respective licenses.
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View details ↗beto-emotion-analysis
finiteautomata基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗beto-sentiment-analysis
finiteautomata**NOTE: this model will be removed soon -- use pysentimiento/robertuito-sentiment-analysis instead** Repository: https://github.com/finiteautomata/pysentimiento/ Model trained with TASS 2020 corpus (around ~5k tweets) of several dialects of Spanish. Base model is BETO, a BERT model trained in Spanish.
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View details ↗Anima-2.9B
fink94基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗This is the Investopedia embedding for finance application by the FinLang team. The model is trained using our open-sourced finance dataset from https://huggingface.co/datasets/FinLang/investopedia-embedding-dataset This is a finetuned embedding model on top of BAAI/bge-base-en-v1.5. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search in RAG applications. This project is for research purposes only. Third-party datasets may be subject to additional terms and conditions under their associated licenses.
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View details ↗yolov8s-seg-solar-panels
finloop基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗finnai-slm-v2
finndot基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗finnai-slm-v3
finndot基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗finnai-slm-v4
finndot基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗byt5-base-finnish
Finnish-NLP基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗gpt2-finnish
Finnish-NLP基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗wav2vec2-large-uralic-voxpopuli-v2-finnish
Finnish-NLP基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗wav2vec2-xlsr-1b-finnish-lm-v2
Finnish-NLP基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗wav2vec2-xlsr-300m-finnish-lm
Finnish-NLP基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗whisper-large-finnish-v3
Finnish-NLP基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Esan_testi
fiojanea基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗FireRed-Image-Edit-1.0
FireRedTeam**FireRed-Image-Edit** is a general-purpose image editing model that delivers high-fidelity and consistent editing across a wide range of scenarios. - **Strong Editing Performance**: FireRed-Image-Edit delivers leading open-source results with accurate instruction following, high image quality, and consistent visual coherence. - **Native Editing Capability**: Built directly from text-to-image foundation model and endowed with editing capabilities. - **Text Style Preservation**: Maintains text styles with high fidelity, achieving performance comparable to closed-source solutions. - **Photo Restoration**: High-quality old photo restoration and enhancement. - **Multi-Image Editing**: Flexible editing of multiple images such as virtual try-on. - 2026.02.14: We released FireRed-Image-Edit-1.0 model weights. Check more details in the Model Zoo section. - 2026.02.10: We released the Technical Report of FireRed-Image-Edit-1.0.
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View details ↗FireRed-Image-Edit-1.0-ComfyUI
FireRedTeam基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗FireRed-Image-Edit-1.0-Lightning
FireRedTeam基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗FireRed-Image-Edit-1.1
FireRedTeamWe introduce FireRed-Image-Edit-1.1, an upgrade to our general-purpose image editing foundation model. Building upon the capabilities presented in the FireRed-Image-Edit-1.0 Technical Report, version 1.1 significantly enhances identity consistency, multi-image conditioning, and domain-specialized editing performance, bringing the model closer to real-world creative production needs. FireRed-Image-Edit establishes a new state-of-the-art among open-source models on Imgedit, Gedit, and RedEdit, while surpassing our closed-source competitors in specific dimensions—a distinction further corroborated by human evaluations highlighting its superior prompt following and visual consistency.
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