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AI 模型 84759

• Qwen3.8-27B-nvfp4↗

  mlx-community

• ModernBERT-base-zeroshot-v2.0↗

  MoritzLaurer

  This model is answerdotai/ModernBERT-base fine-tuned on the same dataset mix as the `zeroshot-v2.0` models in the Zeroshot Classifiers Collection. The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 128 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 2

• aira-socratic-8b-GGUF↗

  mradermacher

• Arabic-English-handwritten-OCR-v3-GGUF↗

  mradermacher

• BiMediX-Bi-i1-GGUF↗

  mradermacher

• bruphin-kappa-i1-GGUF↗

  mradermacher

• C4AI-dpo-model-GGUF↗

  mradermacher

• Copus-2x8B-i1-GGUF↗

  mradermacher

• Decision-WAF-V1.1-0.8B-GGUF↗

  mradermacher

• DeepSeek-R1-Distill-Qwen-7B-GGUF↗

  mradermacher

  weighted/imatrix quants are available at https://huggingface.co/mradermacher/DeepSeek-R1-Distill-Qwen-7B-i1-GGUF If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files. (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)