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@@ -21,13 +21,19 @@ We explore supervised multitask pre-training by proposing ***Instruction Pre-Tra
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/66711d2ee12fa6cc5f5dfc89/vRdsFIVQptbNaGiZ18Lih.png" width="400">
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  </p>
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  ## Resources
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  **🤗 We share our data and models with example usages, feel free to open any issues or discussions! 🤗**
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  - Context-Based Instruction Synthesizer: [instruction-synthesizer](https://huggingface.co/instruction-pretrain/instruction-synthesizer)
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  - Fine-Tuning Data for the Synthesizer: [ft-instruction-synthesizer-collection](https://huggingface.co/datasets/instruction-pretrain/ft-instruction-synthesizer-collection)
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- - General Models Pre-Trained from Scratch:
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  - [InstructLM-500M](https://huggingface.co/instruction-pretrain/InstructLM-500M)
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  - [InstructLM-1.3B](https://huggingface.co/instruction-pretrain/InstructLM-1.3B)
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  - Domain-Specific Models Pre-Trained from Llama3-8B:
@@ -36,7 +42,6 @@ We explore supervised multitask pre-training by proposing ***Instruction Pre-Tra
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  - General Instruction-Augmented Corpora: [general-instruction-augmented-corpora](https://huggingface.co/datasets/instruction-pretrain/general-instruction-augmented-corpora)
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  - Domain-Specific Instruction-Augmented Corpora (no finance data to avoid ethical issues): [medicine-instruction-augmented-corpora](https://huggingface.co/datasets/instruction-pretrain/medicine-instruction-augmented-corpora)
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-
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  ## Domain-Adaptive Continued Pre-Training
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  Following [AdaptLLM](https://huggingface.co/AdaptLLM/medicine-chat), we augment the domain-specific raw corpora with instruction-response pairs generated by our [context-based instruction synthesizer](https://huggingface.co/instruction-pretrain/instruction-synthesizer).
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/66711d2ee12fa6cc5f5dfc89/vRdsFIVQptbNaGiZ18Lih.png" width="400">
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  </p>
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+ **************************** **Updates** ****************************
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+ * 2024/7/15: We scaled up the pre-trained tokens from 100B to 250B, with the number of synthesized instruction-response pairs reaching 500M! Below, we show the performance trend on downstream tasks throughout the pre-training process:
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+ <p align='center'>
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/66711d2ee12fa6cc5f5dfc89/0okCfRkC6uALTfuNxt0Fa.png" width="700">
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+ </p>
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+ * 2024/6/21: Released the [paper](https://huggingface.co/papers/2406.14491), [code](https://github.com/microsoft/LMOps), and [resources](https://huggingface.co/instruction-pretrain)
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  ## Resources
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  **🤗 We share our data and models with example usages, feel free to open any issues or discussions! 🤗**
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  - Context-Based Instruction Synthesizer: [instruction-synthesizer](https://huggingface.co/instruction-pretrain/instruction-synthesizer)
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  - Fine-Tuning Data for the Synthesizer: [ft-instruction-synthesizer-collection](https://huggingface.co/datasets/instruction-pretrain/ft-instruction-synthesizer-collection)
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+ - General Models Pre-Trained from Scratch (on 100B tokes):
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  - [InstructLM-500M](https://huggingface.co/instruction-pretrain/InstructLM-500M)
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  - [InstructLM-1.3B](https://huggingface.co/instruction-pretrain/InstructLM-1.3B)
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  - Domain-Specific Models Pre-Trained from Llama3-8B:
 
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  - General Instruction-Augmented Corpora: [general-instruction-augmented-corpora](https://huggingface.co/datasets/instruction-pretrain/general-instruction-augmented-corpora)
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  - Domain-Specific Instruction-Augmented Corpora (no finance data to avoid ethical issues): [medicine-instruction-augmented-corpora](https://huggingface.co/datasets/instruction-pretrain/medicine-instruction-augmented-corpora)
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  ## Domain-Adaptive Continued Pre-Training
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  Following [AdaptLLM](https://huggingface.co/AdaptLLM/medicine-chat), we augment the domain-specific raw corpora with instruction-response pairs generated by our [context-based instruction synthesizer](https://huggingface.co/instruction-pretrain/instruction-synthesizer).
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