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biu-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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Explore AI models 2428
rubert-base-cased-sentiment
blanchefortThis is a DeepPavlov/rubert-base-cased-conversational model trained on aggregated corpus of 351.797 texts. > Рубцова Ю. Автоматическое построение и анализ корпуса коротких текстов (постов микроблогов) для задачи разработки и тренировки тонового классификатора //Инженерия знаний и технологии семантического веба. – 2012. – Т. 1. – С. 109-116. > RuReviews: An Automatically Annotated Sentiment Analysis Dataset for Product Reviews in Russian.
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View details ↗rubert-base-cased-sentiment-rusentiment
blanchefort> A. Rogers A. Romanov A. Rumshisky S. Volkova M. Gronas A. Gribov RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian. Proceedings of COLING 2018.
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View details ↗Medical-NER
blaze999This model is a fine-tuned version of DeBERTa on the PubMED Dataset. The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 30 - mixed_precision_training: Native AMP The easiest way is to load the inference api from huggingface and second method is through the pipeline object offered by transformers library.
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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 ↗Qwen3-Reranker-4B-W4A16-G128
boboliu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 ↗bert-emotion
boltuix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 ↗bert-lite
boltuix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 ↗bert-mini
boltuix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 ↗NeuroBERT-NER
boltuixThe `boltuix/NeuroBERT-NER` model is a fine-tuned transformer for **Named Entity Recognition (NER)**, built on the `boltuix/NeuroBERT-Mini` base model. It excels at identifying 36 entity types (e.g., people, places, organizations, dates, money) in English text, making it ideal for applications like information extraction, chatbots, and knowledge graph construction. - **Dataset**: boltuix/conll2025-ner (143,709 entries, 6.38 MB) - **Entity Types**: 36 NER tags (18 entity categories with B-/I- tags + O) - **Training Examples**: ~115,812 | **Validation**: ~15,680 | **Test**: ~12,217 *Note*: Split sizes are approximate and don’t sum to 143,709; verify with dataset analysis. - **Domains**: News, user-generated content, research corpora - **Tasks**: Sentence-level and document-level NER - **Version**: v1.1 > **Note**: The dataset link is a placeholder. Replace with the correct Hugging Face repository URL once available.
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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 ↗jiwo-0.8b-GGUF
breaksoftware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 ↗bsc-bio-ehr-es-carmen-anon
BSC-NLP4BIA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 ↗bsc-bio-ehr-es-meddocan
BSC-NLP4BIA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 ↗politicalBiasBERT
bucketresearch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 ↗rubert-tiny2-russe-toxicity
BunnyNoBugsThis model is a fine-tuned version of cointegrated/rubert-tiny2 on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2087 - Precision Macro: 0.9395 - Recall Macro: 0.9394 - F1 Macro: 0.9394 - F1 Neutral: 0.9398 - F1 Toxic: 0.9390 The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10
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View details ↗clinical-assertion-negation-bert
bvanaken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 ↗NusaBert-ner-v1.3
cahya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 ↗Eikos-27B
caiovicentino1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 ↗Eikos-4B
caiovicentino1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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