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AI 모델 84759

• y5↗

  tao1000

• Nous-Hermes-Llama-2-7B-GGUF↗

  TheBloke

• FLUX.2-klein-9B-manga-colorization-by-reference-LORA↗

  thedeoxen

• vit_base_patch16_224_miil.in21k_ft_in1k↗

  timm

• quartz-micro-preview-v3-base↗

  VertexAGI

• kolibri-vikhr-mistral-0427↗

  Vikhrmodels

  This is an instruction following model (based on Vikhr Base) optimized for Russian language. It was trained using kolibrify via curriculum learning on a multitude of instruction datasets. The model uses ChatML template. It was trained to be sensitive to the system prompt, experiment with it. Primary uses: information retrieval, classification, semantic analysis, translation (en-ru), etc. Currently in pre-alpha.

• 3Danimation↗

  Yntec

• zerank-2-reranker↗

  zeroentropy

  In search engines, rerankers are crucial for improving the accuracy of your retrieval system. However, SOTA rerankers are closed-source and proprietary. At ZeroEntropy, we've trained a SOTA reranker outperforming closed-source competitors, and we're launching our model here on HuggingFace. This reranker outperforms proprietary rerankers such as `cohere-rerank-v3.5` and `gemini-2.5-flash` across a wide variety of domains, including finance, legal, code, STEM, medical, and conversational data.

• tinybert-emotion-balanced↗

  AdamCodd

  This model is a fine-tuned version of bert-tiny on the emotion balanced dataset. It achieves the following results on the evaluation set: - Loss: 0.1809 - Accuracy: 0.9354 TinyBERT is 7.5 times smaller and 9.4 times faster on inference compared to its teacher BERT model (while DistilBERT is 40% smaller and 1.6 times faster than BERT). The model has been trained on 89_754 examples split into train, validation and test. Each label was perfectly balanced in each split. This model is not as accurate as the distilbert-emotion-balanced one because the focus was on speed, which can lead to misinterpretation of complex sentences. Despite this, its performance is quite good and should be more than sufficient for most use cases.

• exp_att_stats_h2oai_h2o-danube3-500m-chat_kmfoda_booksum_100_1000_4↗

  alessiodevoto