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  # GPT2 Zinc 87m
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- This is a GPT2 style autoregressive language model trained on ~480m SMILES strings from the [ZINC database](https://zinc.docking.org/) available through [Huggingface](https://huggingface.co/entropy/gpt2_zinc_87m).
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  The model has ~87m parameters and was trained for 175000 iterations with a batch size of 3072 to a validation loss of ~.615. This model is useful for generating druglike molecules or generating embeddings from SMILES strings
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  ## How to use
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- To use, install the [transformers](https://github.com/huggingface/transformers) library:
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-
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- ```
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- pip install transformers
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- ```
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-
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- Load the model from the Huggingface Hub:
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  ```python
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  from transformers import GPT2TokenizerFast, GPT2LMHeadModel
 
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  # GPT2 Zinc 87m
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+ This is a GPT2 style autoregressive language model trained on ~480m SMILES strings from the [ZINC database](https://zinc.docking.org/).
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  The model has ~87m parameters and was trained for 175000 iterations with a batch size of 3072 to a validation loss of ~.615. This model is useful for generating druglike molecules or generating embeddings from SMILES strings
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  ## How to use
 
 
 
 
 
 
 
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  ```python
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  from transformers import GPT2TokenizerFast, GPT2LMHeadModel