readme

README.md

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+---
+language:
+- en
+- zh
+library_name: transformers
+tags:
+- Long Context
+- chatglm
+- llama
+datasets:
+- THUDM/LongAlign-10k
+- THUDM/LongBench
+---
+# LongAlign-7B-64k
+
+<p align="center">
+  🤗 <a href="https://huggingface.co/datasets/THUDM/LongAlign-10k" target="_blank">[LongAlign Dataset] </a> • 💻 <a href="https://github.com/THUDM/LongAlign" target="_blank">[Github Repo]</a> • 📃 <a href="https://arxiv.org/" target="_blank">[LongAlign Paper]</a> 
+</p>
+
+**LongAlign** is the first full recipe for LLM alignment on long context. We propose the **LongAlign-10k** dataset, containing 10,000 long instruction data of 8k-64k in length. We investigate on trianing strategies, namely **packing (with loss weighting) and sorted batching**, which are all implemented in our code. For real-world long context evaluation, we introduce **Chat-LongBench** that evaluate the instruction-following capability on queries of 10k-100k length.
+
+## All Models
+
+We open-sourced the following list of models:
+
+|Model|Huggingface Repo|Description|
+|---|---|---|
+|**LongAlign-6B-64k-base**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-6B-64k-base) | **ChatGLM3-6B** with an extended 64k context window |
+|**LongAlign-6B-64k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-6B-64k) | Chat model by LongAlign training on LongAlign-6B-64k-base|
+|**LongAlign-7B-64k-base**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-7B-64k-base) | **Llama-2-7B** with an extended 64k context window |
+|**LongAlign-7B-64k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-7B-64k) | Chat model by LongAlign training on LongAlign-7B-64k-base|
+|**LongAlign-13B-64k-base**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-13B-64k-base) | **Llama-2-13B** with an extended 64k context window |
+|**LongAlign-13B-64k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-13B-64k) | Chat model by LongAlign training on LongAlign-13B-64k-base|
+|**ChatGLM3-6B-128k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/chatglm3-6b-128k) | **ChatGLM3-6B** with a 128k context window|
+
+![](assets/leaderboard.png)
+
+## Model usage
+Chat prompt template for LongAlign-6B-64k:
+```text
+[Round 1]
+
+问：Hi!
+
+答：Hello! What can I assist you today?
+
+[Round 2]
+
+问：What should I do if I can't sleep at night?
+
+答：
+```
+Chat prompt template for LongAlign-7B-64k and LongAlign-13B-64k:
+```text
+[INST]Hi![/INST]Hello! What can I assist you today?
+
+[INST]What should I do if I can't sleep at night?[/INST]
+```
+ChatGLM3-6B-128k uses the same prompt template as [ChatGLM3-6B](https://huggingface.co/THUDM/chatglm3-6b).
+
+A simple demo for deployment of the model:
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+tokenizer = AutoTokenizer.from_pretrained("THUDM/LongAlign-6B-64k", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("THUDM/LongAlign-6B-64k", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
+model = model.eval()
+query = open("assets/paper.txt").read() + "\n\nPlease summarize the paper."
+response, history = model.chat(tokenizer, query, history=[], max_new_tokens=512, temperature=1)
+print(response)
+```
+
+## Citation
+
+If you find our work useful, please consider citing LongAlign:
+
+```
+
+```