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+*This model was published in HF papers on 2023-09-09 and contributed to Hugging Face Transformers on 2023-11-28.*
+
+# MADLAD-400
+
+
+## Overview
+
+MADLAD-400 models were released in the paper [MADLAD-400: A Multilingual And Document-Level Large Audited Dataset](https://huggingface.co/papers/2309.04662).
+
+The abstract from the paper is the following:
+
+*We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss
+the limitations revealed by self-auditing MADLAD-400, and the role data auditing
+had in the dataset creation process. We then train and release a 10.7B-parameter
+multilingual machine translation model on 250 billion tokens covering over 450
+languages using publicly available data, and find that it is competitive with models
+that are significantly larger, and report the results on different domains. In addition, we train a 8B-parameter language model, and assess the results on few-shot
+translation. We make the baseline models 1
+available to the research community.*
+
+This model was added by [Juarez Bochi](https://huggingface.co/jbochi). The original checkpoints can be found [here](https://github.com/google-research/google-research/tree/master/madlad_400).
+
+This is a machine translation model that supports many low-resource languages, and that is competitive with models that are significantly larger.
+
+One can directly use MADLAD-400 weights without finetuning the model:
+
+```python
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+
+model = AutoModelForSeq2SeqLM.from_pretrained("google/madlad400-3b-mt", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("google/madlad400-3b-mt")
+
+inputs = tokenizer("<2pt> I love pizza!", return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs)
+print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
+['Eu amo pizza!']
+```
+
+Google has released the following variants:
+
+- [google/madlad400-3b-mt](https://huggingface.co/google/madlad400-3b-mt)
+
+- [google/madlad400-7b-mt](https://huggingface.co/google/madlad400-7b-mt)
+
+- [google/madlad400-7b-mt-bt](https://huggingface.co/google/madlad400-7b-mt-bt)
+
+- [google/madlad400-10b-mt](https://huggingface.co/google/madlad400-10b-mt)
+
+The original checkpoints can be found [here](https://github.com/google-research/google-research/tree/master/madlad_400).
+
+<Tip>
+
+Refer to [T5's documentation page](t5) for all API references, code examples, and notebooks. For more details regarding training and evaluation of the MADLAD-400, refer to the model card.
+
+</Tip>