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Model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct Source: Original Platform
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README.md
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---
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license: llama3
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datasets:
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- princeton-nlp/prolong-data-64K
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- princeton-nlp/prolong-data-512K
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- HuggingFaceH4/ultrachat_200k
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base_model:
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- princeton-nlp/Llama-3-8B-ProLong-512k-Base
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---
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# princeton_nlp/Llama-3-8B-ProLong-512k-Instruct
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[[Paper](https://arxiv.org/pdf/2410.02660)] [[HF Collection](https://huggingface.co/collections/princeton-nlp/prolong-66c72d55d2051a86ac7bd7e4)] [[Code](https://github.com/princeton-nlp/ProLong)]
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**ProLong** (<u>Pr</u>incet<u>o</u>n <u>long</u>-context language models) is a family of long-context models that are continued trained and supervised fine-tuned from Llama-3-8B, with a maximum context window of 512K tokens. Our [main ProLong model](https://huggingface.co/princeton-nlp/Llama-3-8B-ProLong-512k-Instruct) is one of the best-performing long-context models at the 10B scale (evaluated by [HELMET](https://github.com/princeton-nlp/helmet)).
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To train this strong long-context model, we conduct thorough ablations on the long-context pre-training data, SFT data, and numerous other design choices. We demonstrate our findings in our paper, [How to Train Long-Context Language Models (Effectively)](https://arxiv.org/pdf/2410.02660).
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Authors: [Tianyu Gao](https://gaotianyu.xyz/about)\*, [Alexander Wettig](https://www.cs.princeton.edu/~awettig/)\*, [Howard Yen](https://howard-yen.github.io/), [Danqi Chen](https://www.cs.princeton.edu/~danqic/) (* equal contribution)
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Contact: `{tianyug, awettig}@princeton.edu`
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## The ProLong Models
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- [princeton_nlp/Llama-3-8B-ProLong-64k-Base](https://huggingface.co/princeton-nlp/Llama-3-8B-ProLong-64k-Base)
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- [princeton_nlp/Llama-3-8B-ProLong-64k-Instruct](https://huggingface.co/princeton-nlp/Llama-3-8B-ProLong-64k-Instruct)
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- [princeton_nlp/Llama-3-8B-ProLong-512k-Base](https://huggingface.co/princeton-nlp/Llama-3-8B-ProLong-512k-Base)
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- ⭐ [princeton_nlp/Llama-3-8B-ProLong-512k-Instruct](https://huggingface.co/princeton-nlp/Llama-3-8B-ProLong-512k-Instruct) ← you are here!
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## Model card
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Here are some quick facts about our main ProLong model: [princeton-nlp/Llama-3-8B-ProLong-512k-Instruct](https://huggingface.co/princeton-nlp/Llama-3-8B-ProLong-512k-Instruct).
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* Base model: [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)
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* Long-context continued training: 20B tokens on 64K training data ([princeton-nlp/prolong-data-64K](https://huggingface.co/datasets/princeton-nlp/prolong-data-64K)), and 20B tokens on 512K training data ([princeton-nlp/prolong-data-512K](https://huggingface.co/datasets/princeton-nlp/prolong-data-512K))
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* Supervised fine-tuning (SFT): [UltraChat](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k)
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* Maximum context window: 512K tokens
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<p align="center" style="margin-bottom: 0;">
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<img width="80%" alt="image" src="https://github.com/user-attachments/assets/c31c9671-49fe-4776-91d2-de70ffd9f9a1">
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</p>
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<p align="center" style="margin-top: 0; padding-top: 0;">
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<em>ProLong performance on <a href="https://github.com/princeton-nlp/helmet">HELMET</a> averaged over 32K, 64K, and 128K lengths. All models are instruct models.</em>
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</p>
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<p align="center">
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<img width="80%" alt="image" src="https://github.com/user-attachments/assets/a36a7d0f-4480-4a29-80f3-208477707fb7">
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</p>
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<p align="center" style="margin-top: 0;">
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<em>ProLong training recipe.</em>
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</p>
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## Citation
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```bibtex
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@article{gao2024prolong,
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title={How to Train Long-Context Language Models (Effectively)},
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author={Gao, Tianyu and Wettig, Alexander and Yen, Howard and Chen, Danqi},
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journal={arXiv preprint arXiv:2410.02660},
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year={2024}
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}
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```
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"model.layers.8.self_attn.o_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.norm.weight": "model-00007-of-00007.safetensors"
|
||||
}
|
||||
}
|
||||
17
special_tokens_map.json
Normal file
17
special_tokens_map.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "!"
|
||||
}
|
||||
410563
tokenizer.json
Normal file
410563
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2063
tokenizer_config.json
Normal file
2063
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user