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dplm_150m

airkingbd

DPLM (diffusion protein language model) is a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequences. Specifically, DPLM exhibits impressive performance in protein sequence generation, motif scaffolding, inverse folding, and representation learning. For more detailed information about DPLM, please refer to our paper Diffusion Language Models Are Versatile Protein Learners. This repository contains the DPLM model checkpoint of 150M parameters. Please refer to our github repository for code and usage. For example, you can load DPLM model as below: All DPLM checkpoints are available in the table below: | Model size | Num layers | Num parameters | |------------------------------|----|----------| | dplm_3b | 36 | 3B | | dplm_650m | 33 | 650M | | dplm_150m | 30 | 150M |

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dplm_3b

airkingbd

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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dplm_650m

airkingbd

DPLM (diffusion protein language model) is a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequences. Specifically, DPLM exhibits impressive performance in protein sequence generation, motif scaffolding, inverse folding, and representation learning. For more detailed information about DPLM, please refer to our paper Diffusion Language Models Are Versatile Protein Learners. This repository contains the DPLM model checkpoint of 650M parameters. Please refer to our github repository for code and usage. For example, you can load DPLM model as below: All DPLM checkpoints are available in the table below: | Model size | Num layers | Num parameters | |------------------------------|----|----------| | dplm_3b | 36 | 3B | | dplm_650m | 33 | 650M | | dplm_150m | 30 | 150M |

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dplm2_650m

airkingbd

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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Category pending
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Price not verifiedCheck multimodal and channel pricing separately
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Source / docs ↗

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。

Basic profile indexed · More details to follow

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗
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1 M = 1 million tokens · USD
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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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