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The paper links the code repo: https://github.com/lovishchopra/NL2FOL

But I don't see a pretrained model in there, so I'm not sure what to pass as `your_nli_model_name`:

  python3 src/nl_to_fol.py --model_name <your_model_name> --nli_model_name <your_nli_model_name> --run_name <run_name> --dataset --length


If we check the script, it seems to support open ai models and llama https://github.com/lovishchopra/NL2FOL/blob/main/src/nl_to_f...

It would have been a lot cooler if this was set up as a pretrained model using RL to translate.


That's for --model_name, not --nli_model_name:

https://github.com/lovishchopra/NL2FOL/blob/4635a81f216da2ad...

    nli_tokenizer = AutoTokenizer.from_pretrained(args.nli_model_name)
    nli_model = AutoModelForSequenceClassification.from_pretrained(args.nli_model_name)


Although not sure, it can be related to NLI models described here https://paperswithcode.com/task/natural-language-inference




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