Dymium-NER-v1
dymium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 ↗DISCOVER & COMPARE
Explore AI models 84995
gemma-4-26b-a4b-it-oQ8e-mtp-drafter
dynamicagency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 ↗Totvs-Protheus-ADVPL-V0.1
dyulianocecilio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 ↗Qwen3.8-Flash-Next-MTP-GGUF
dzannottiThe multi-token-prediction head that ships inside Qwen/Qwen3.8-Flash-Next: one full `qwen4exp` block (attention + 512-expert MoE + hyper-connections, 4B parameters), trained jointly with the model. The upstream converter (PR 27742) drops it, so the popular GGUFs have none. This one is exported straight from the bf16 checkpoint and quantized with plain `llama-quantize`, so it runs on stock llama.cpp kernels (any backend), not a fork's quant types. **This is a draft head, not a model.** Use it as `-md` next to any Flash-Next GGUF target (tested with unsloth's UD-Q4_K_XL and UD-IQ4_XS). Set `LLAMA_ATTN_ROT_DISABLE=1`: upstream's quantized-KV activation rotation (#21038) is not supported by the qwen4exp attention path and the server aborts at load without it.
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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 ↗Vexion-gpt-medium
DZER-Studios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 ↗GIGABATEMAN-7B-GGUF
DZgas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 ↗Tower-Plus-2B-GGUF
DZgas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 ↗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 ↗granite-4.1-3b-GGUF
Dzluck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 ↗qwen35-claude-coder-GGUF
Dzluck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 ↗font-architect
dzungpham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 ↗Polaris-4B-Preview-IQ-GGUF
dzur658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 ↗inclusively-classification
E-MIMICThis model is an Italian classification model fine-tuned from the Italian BERT model for the classification of inclusive language in Italian. It has been trained to detect three classes: - `inclusive`: the sentence is inclusive (e.g. "Il personale docente e non docente") - `not_inclusive`: the sentence is not inclusive (e.g. "I professori") - `not_pertinent`: the sentence is not pertinent to the task (e.g. "La scuola è chiusa") The model has been trained on a dataset containing: - 8580 training sentences - 1073 validation sentences - 1072 test sentences
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View details ↗This model is an Italian sequence-to-sequence model fine-tuned from the IT5-large for the task of inclusive language rewriting. It has been trained to analyze and rewrite sentences in Italian to make them more inclusive (if needed). For example, the sentence `I professori devono essere preparati` (The professors must be prepared) is rewritten as `Il personale docente deve essere preparato` (The teaching staff must be prepared).
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View details ↗Krea-2-Pixel-Art
e-n-v-y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 ↗Qwen-Image-2.1-Fix
e-n-v-yA lora that, when used with the proper settings, fixes most of the image generation issues with Qwen Image 2.1. Download the workflow zip for the correct settings. Images are comparisons between vanilla settings w/ no lora and using the lora with the recommended settings.
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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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