c67-h38
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c67-h40
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View details ↗c69-h4
aalv2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 ↗c71-h32
aalv2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 ↗c71-h4
aalv2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 ↗email-phishing-distilbert-finetuned
aamoshdahal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 ↗bge-m3-onnx
aapot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 ↗sarvam-105b-GGUF-IQ2_M-IQ1_M
Aaravomega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 ↗sarvam-30b-GGUF-IQ2_M-IQ1_M
Aaravomega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 ↗German_Semantic_STS_V2
aari1995**Note:** Check out my new, updated models: German_Semantic_V3 and V3b! This is a sentence-transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search. Special thanks to deepset for providing the model gBERT-large and also to Philip May for the Translation of the dataset and chats about the topic.
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View details ↗German_Semantic_V3
aari1995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 ↗German_Semantic_V3b
aari1995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 ↗gpt2-japanese-20k-lc
aariciah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 ↗gpt2-japanese-dutch-routed
aariciah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 ↗gpt2-portuguese-20k-lc
aariciah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 ↗gpt2-russian-20k-lc
aariciah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 ↗gpt2-spanish-20k-lc
aariciah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 ↗gpt2-turkish-20k-lc
aariciah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 ↗peptideclm-2-hybrid-base
aaronfellerThis model is part of the **PeptideMTR** suite, to be released in a forthcoming paper. It is designed for multi-target biochemical property prediction. - **Architecture:** BERT-based Transformer - **Pretraining:** MLM-MTR - **Input:** SMILES string All models in this suite are designed for simplicity. For inference, the model accepts a SMILES string directly.
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View details ↗peptideclm-2-mlm-base
aaronfellerThis model is part of the **PeptideMTR** suite, to be released in a forthcoming paper. It is designed for multi-target biochemical property prediction. - **Architecture:** BERT-based Transformer - **Pretraining:** MLM - **Input:** SMILES string All models in this suite are designed for simplicity. For inference, the model accepts a SMILES string directly.
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