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README.md

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 pipeline_tag: text-generation
 tags:
 - text-generation-inference
+- backpack
+- backpackmodel
 library_name: transformers
----
+license: apache-2.0
+datasets:
+- openwebtext
+language:
+- en
+---
+
+---
+
+---
+
+
+# Model Card for Backpack-GPT2
+
+<!-- Provide a quick summary of what the model is/does. [Optional] -->
+The Backpack-GPT2 language model is an instance of the [Backpack architecture](https://arxiv.org/abs/2305.16765), intended to combine strong modeling performance with an interface for interpretability and control.
+Most details about this model and its training should be accessed in the paper, [Backpack Language Models](https://arxiv.org/abs/2305.16765).
+
+See also [backpackmodels.science](backpackmodels.science).
+
+#  Table of Contents
+
+- [Model Card for Backpack-GPT2](#model-card-for--model_id-)
+- [Table of Contents](#table-of-contents)
+- [Model Details](#model-details)
+  - [Model Description](#model-description)
+- [Uses](#uses)
+- [Bias, Risks, and Limitations](#bias-risks-and-limitations)
+- [Training Details](#training-details)
+  - [Training Data](#training-data)
+  - [Training Procedure](#training-procedure)
+- [Environmental Impact](#environmental-impact)
+- [Technical Specifications [optional]](#technical-specifications-optional)
+  - [Model Architecture and Objective](#model-architecture-and-objective)
+  - [Compute Infrastructure](#compute-infrastructure)
+    - [Hardware](#hardware)
+    - [Software](#software)
+- [Citation](#citation)
+- [Model Card Authors [optional]](#model-card-authors-optional)
+- [Model Card Contact](#model-card-contact)
+- [How to Get Started with the Model](#how-to-get-started-with-the-model)
+
+
+# Model Details
+
+## Model Description
+
+<!-- Provide a longer summary of what this model is/does. -->
+The Backpack-GPT2 is a [Backpack-based language model](https://arxiv.org/abs/2305.16765), an architecture intended to combine strong modeling performance with an interface for interpretability and control.
+
+- **Developed by:**  John Hewitt, John Thickstun, Christopher D. Manning, Percy Liang
+- **Shared by [Optional]:** More information needed
+- **Model type:** Language model
+- **Language(s) (NLP):** en
+- **License:** apache-2.0
+- **Resources for more information:**
+    - [GitHub Repo](https://github.com/john-hewitt/backpacks-flash-attn)
+    - [Associated Paper](https://huggingface.co/datasets/openwebtext)
+
+# Uses
+
+This model is intended for use in the study and development of increasingly interpretable methods in natural language processing.
+It is not directly fit for any production use.
+
+
+# Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
+This model in particular is limited in its capabilities, and with a brand new architecture, less is known about its biases than, e.g., Transformer-based models.
+
+
+# Training Details
+
+## Training Data
+
+<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+This model was trained on the [OpenWebText](https://huggingface.co/datasets/openwebtext) corpus.
+
+
+## Training Procedure
+
+This model was trained for 100k gradient steps with a batch size of 512k tokens and a linearly decaying learning rate from 6e-4 to zero, with a linear warmup of 5k steps.
+
+# Environmental Impact
+
+- **Hardware Type:** 4 A100 GPUs (40G)
+- **Hours used:** Roughly 4 days.
+- **Cloud Provider:** Stanford compute.
+- **Compute Region:** Stanford energy grid.
+
+## Model Architecture and Objective
+
+This model was trained to minimize the cross-entropy loss, and is a [Backpack language model](https://arxiv.org/pdf/2305.16765.pdf).
+
+## Compute Infrastructure
+
+This model was trained on a slurm cluster.
+
+### Hardware
+
+This model was trained on 4 A100s.
+
+### Software
+
+This model was trained with [FlashAttention](https://github.com/HazyResearch/flash-attention) and [PyTorch](https://pytorch.org/)
+
+# Citation
+
+**BibTeX:**
+
+```
+@InProceedings{hewitt2023backpack,
+  author =      "Hewitt, John and Thickstun, John and Manning, Christopher D. and Liang, Percy",
+  title =       "Backpack Language Models",
+  booktitle =   "Proceedings of the Association for Computational Linguistics",
+  year =        "2023",
+  publisher =   "Association for Computational Linguistics",
+  location =    "Toronto, Canada",
+}
+```
+
+
+# Model Card Authors [optional]
+
+<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->
+
+John Hewitt
+
+# Model Card Contact
+
+johnhew@cs.stanford.edu
+
+# How to Get Started with the Model
+
+
+
+
+<details>
+<summary> Click to expand </summary>
+
+More information needed
+
+</details>