molcrawl-compounds-guacamol-gpt2-small/README.md

license, tags, pipeline_tag

license	tags	pipeline_tag
apache-2.0	pytorch gpt2 molecule-compound	text-generation

molcrawl-compounds-guacamol-gpt2-small

Model Description

GPT-2 small (124M parameters) fine-tuned on GuacaMol SMILES data, starting from the molcrawl-compounds-gpt2-small pre-trained model.

The tokenizer is a character-level BPE tokenizer (vocab_size=612). Input SMILES strings should be passed without spaces. The [SEP] token (id=13) is used as the end-of-sequence marker.

Datasets

• GuacaMol: https://github.com/BenevolentAI/guacamol (Fine-tuning dataset)

• Model Type: gpt2

• Data Type: Molecule/Compound

• Training Date: 2026-04-24

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained("kojima-lab/molcrawl-compounds-guacamol-gpt2-small")
tokenizer = AutoTokenizer.from_pretrained("kojima-lab/molcrawl-compounds-guacamol-gpt2-small")

# Generate SMILES string
prompt = "CC(=O)O"
input_ids = tokenizer.encode(prompt, return_tensors="pt")
with torch.no_grad():
    output_ids = model.generate(
        input_ids,
        max_new_tokens=50,
        do_sample=True,
        temperature=0.8,
        eos_token_id=tokenizer.convert_tokens_to_ids("[SEP]"),  # [SEP] is EOS for compounds
        pad_token_id=0,
    )
print(tokenizer.decode(output_ids[0], skip_special_tokens=True))

Source Code

Training pipeline, configuration files, and data preparation scripts are available in the MolCrawl GitHub repository: https://github.com/mmai-framework-lab/MolCrawl

License

This model is released under the APACHE-2.0 license.

Citation

If you use this model, please cite:

@misc{molcrawl_compounds_guacamol_gpt2_small,
  title={molcrawl-compounds-guacamol-gpt2-small},
  author={{RIKEN}},
  year={2026},
  publisher={{Hugging Face}},
  url={{https://huggingface.co/kojima-lab/molcrawl-compounds-guacamol-gpt2-small}}
}