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transformers/docs/source/en/model_doc/mpt.md

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+*This model was released on 2023-05-05 and added to Hugging Face Transformers on 2023-07-25.*
+
+# MPT
+
+<div class="flex flex-wrap space-x-1">
+<img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white">
+</div>
+
+## Overview
+
+The MPT model was proposed by the [MosaicML](https://www.mosaicml.com/) team and released with multiple sizes and finetuned variants. The MPT models are a series of open source and commercially usable LLMs pre-trained on 1T tokens.
+
+MPT models are GPT-style decoder-only transformers with several improvements: performance-optimized layer implementations, architecture changes that provide greater training stability, and the elimination of context length limits by replacing positional embeddings with ALiBi.
+
+- MPT base: MPT base pre-trained models on next token prediction
+- MPT instruct: MPT base models fine-tuned on instruction based tasks
+- MPT storywriter: MPT base models fine-tuned for 2500 steps on 65k-token excerpts of fiction books contained in the books3 corpus, this enables the model to handle very long sequences
+
+The original code is available at the  [`llm-foundry`](https://github.com/mosaicml/llm-foundry/tree/main) repository.
+
+Read more about it [in the release blogpost](https://www.mosaicml.com/blog/mpt-7b)
+
+## Usage tips
+
+- Learn more about some techniques behind training of the model [in this section of llm-foundry repository](https://github.com/mosaicml/llm-foundry/blob/main/TUTORIAL.md#faqs)
+- If you want to use the advanced version of the model (triton kernels, direct flash attention integration), you can still use the original model implementation by adding `trust_remote_code=True` when calling `from_pretrained`.
+
+## Resources
+
+- [Fine-tuning Notebook](https://colab.research.google.com/drive/1HCpQkLL7UXW8xJUJJ29X7QAeNJKO0frZ?usp=sharing) on how to fine-tune MPT-7B on a free Google Colab instance to turn the model into a Chatbot.
+
+## MptConfig
+
+[[autodoc]] MptConfig
+    - all
+
+## MptModel
+
+[[autodoc]] MptModel
+    - forward
+
+## MptForCausalLM
+
+[[autodoc]] MptForCausalLM
+    - forward
+
+## MptForSequenceClassification
+
+[[autodoc]] MptForSequenceClassification
+    - forward
+
+## MptForTokenClassification
+
+[[autodoc]] MptForTokenClassification
+    - forward
+
+## MptForQuestionAnswering
+
+[[autodoc]] MptForQuestionAnswering
+    - forward