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license: apache-2.0
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library_name: transformers
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pipeline_tag: feature-extraction
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tags:
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- chemistry
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- transformers
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---
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# selfies-ted2m
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selfies-ted is an transformer based encoder decoder model for molecular representations using SELFIES. This is a 2.2M parameter version of the model. For the full-sized version and more
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This version also includes a projection layer to convert the last hidden state of the BART model (256-dimensional vector per token) to a single 128-dimension vector for the whole SELFIES sequence.
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---
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license: apache-2.0
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library_name: transformers
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pipeline_tag: feature-extraction
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tags:
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- chemistry
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- transformers
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---
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# selfies-ted2m
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selfies-ted is an transformer based encoder decoder model for molecular representations using SELFIES. This is a 2.2M parameter version of the model. For the full-sized version and more information on architecture, see [selfies-ted](https://huggingface.co/ibm-research/materials.selfies-ted).
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This version also includes a projection layer to convert the last hidden state of the BART model (256-dimensional vector per token) to a single 128-dimension vector for the whole SELFIES sequence.
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