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AI 모델 84759

• sarvam-translate-GGUF↗

  Mungert

• Qwen3.8-Flash-Next-MTP-GGUF↗

  mxxm-t

• Qari-OCR-0.4.0-VL-4B-Instruct↗

  NAMAA-Space

• Custodes-SDXL-LoRA-Warhammer-40k↗

  nDimensional

• claim-photo-integrity-detector↗

  obuladinnesai

• Llama-3.2-1B-Instruct-ONNX↗

  onnx-community

• gpt-3.5-turbo-0301↗

  OpenAI

• plamo-13b↗

  pfnet

• senda↗

  pin

• PubMedBERT-MNLI-MedNLI↗

  pritamdeka

  This model is a fine-tuned version of PubMedBERT on the MNLI dataset first and then on the MedNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.9501 - Accuracy: 0.8667 The model can be used for NLI tasks related to biomedical data and even be adapted to fact-checking tasks. It can be used from the Huggingface pipeline method as follows: The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20.0