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+ ---
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+ # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
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+ # Doc / guide: https://huggingface.co/docs/hub/model-cards
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+ {}
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+ ---
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+
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+ # Model Card for *NoShuffle* GPT-2 (without Positional Encodings)
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+ This is one model in a collection of models trained on the impossible
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+ languages of [Kallini et al. 2024](https://arxiv.org/abs/2401.06416).
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+
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+ This model is a GPT-2 Small model trained *without positional encodings*
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+ from scratch on the ***NoShuffle***
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+ language. We include a total of 30 checkpoints over the course of
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+ model training, from step 100 to 3000 in increments of 100 steps.
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+ The main branch contains the final checkpoint (3000), and the other
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+ checkpoints are accessible as revisions.
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+
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+ ![languages.png](https://cdn-uploads.huggingface.co/production/uploads/6268bc06adb1c6525b3d5157/pBt38YYQL1gj8DqjyorWS.png)
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+
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+ ## Model Details
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+
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+ - **Developed by:** Julie Kallini, Isabel Papadimitriou, Richard Futrell, Kyle Mahowald, Christopher Potts
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+ - **Model type:** Causal Language Model
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+ - **Language(s) (NLP):** English
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+ - **GitHub Repository:** https://github.com/jkallini/mission-impossible-language-models
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+ - **Paper:** https://arxiv.org/pdf/2401.06416
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+
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+ ## Uses
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+
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+ This artefact is solely intended for the study of language learning
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+ and acquisition in computational models. It should not be
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+ used in any production setting.
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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ **Important:** This will download our modified GPT-2 code that does
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+ not have absolute positional encodings. If using this model in the
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+ same environment as another GPT-2 model with positional encodings,
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+ load the second model as a `GPT2Model` explicitly.
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+
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+ ```python
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+ from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+
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+ # Load model and tokenizer
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+ model_id = "mission-impossible-lms/no-shuffle-gpt2-no-pos"
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+ model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
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+ tokenizer = AutoTokenizer.from_pretrained(model_id)
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+
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+ # Set up the prompt and encode it
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+ prompt = "He clean"
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+ inputs = tokenizer(prompt, return_tensors="pt")
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+
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+ # Generate text
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+ output = model.generate(inputs.input_ids, max_length=20)
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+
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+ # Decode and print the generated text
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+ generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
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+ print(generated_text)
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+ ```
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+
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+ By default, the `main` branch of this model repo loads the
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+ last model checkpoint (3000). To access the other checkpoints,
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+ use the `revision` argument:
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+
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+ ```
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+ model = GPT2LMHeadModel.from_pretrained(model_id, revision="checkpoint-500")
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+ ```
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+ This loads the model at checkpoint 500.
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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+ This model was trained on the [100M-word BabyLM dataset](https://babylm.github.io/).
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+ Before training, we first transform the dataset into
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+ the corresponding impossible language, as described in
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+ our paper.
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+
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+ ### Training Procedure
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+
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+ This model was trained for 3,000 gradient steps with
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+ a batch size of 2^19 tokens. We train with a learning
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+ rate that linearly warms up from 0 to 6e-4 over 300 steps.
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+
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+ ## Environmental Impact
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+
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+ - **Hardware Type:** NVIDIA RTX 3090 (24GB) + NVIDIA RTX A6000 (48GB) GPUs.
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+ - **Hours used:** ~24 hours.
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @inproceedings{kallini-etal-2024-mission,
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+ title = "Mission: Impossible Language Models",
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+ author = "Kallini, Julie and
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+ Papadimitriou, Isabel and
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+ Futrell, Richard and
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+ Mahowald, Kyle and
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+ Potts, Christopher",
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+ editor = "Ku, Lun-Wei and
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+ Martins, Andre and
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+ Srikumar, Vivek",
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+ booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
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+ month = aug,
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+ year = "2024",
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+ address = "Bangkok, Thailand",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2024.acl-long.787",
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+ doi = "10.18653/v1/2024.acl-long.787",
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+ pages = "14691--14714",
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+ }
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+ ```
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+
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+ ## Model Card Authors
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+
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+ Julie Kallini
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+
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+ ## Model Card Contact
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+
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+ kallini@stanford.edu