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Browse files- README.md +79 -0
- assets/leaderboard.png +0 -0
- config.json +28 -0
- generation_config.json +9 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +35 -0
README.md
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---
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language:
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- en
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- zh
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library_name: transformers
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tags:
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- Long Context
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- chatglm
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- llama
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datasets:
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- THUDM/LongAlign-10k
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- THUDM/LongBench
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---
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# LongAlign-13B-64k-base
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<p align="center">
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🤗 <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>
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</p>
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**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.
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## All Models
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We open-sourced the following list of models:
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|Model|Huggingface Repo|Description|
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|---|---|---|
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|**LongAlign-6B-64k-base**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-6B-64k-base) | **ChatGLM3-6B** with an extended 64k context window |
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|**LongAlign-6B-64k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-6B-64k) | Chat model by LongAlign training on LongAlign-6B-64k-base|
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|**LongAlign-7B-64k-base**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-7B-64k-base) | **Llama-2-7B** with an extended 64k context window |
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|**LongAlign-7B-64k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-7B-64k) | Chat model by LongAlign training on LongAlign-7B-64k-base|
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|**LongAlign-13B-64k-base**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-13B-64k-base) | **Llama-2-13B** with an extended 64k context window |
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|**LongAlign-13B-64k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/LongAlign-13B-64k) | Chat model by LongAlign training on LongAlign-13B-64k-base|
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|**ChatGLM3-6B-128k**| [🤗 Huggingface Repo](https://huggingface.co/THUDM/chatglm3-6b-128k) | **ChatGLM3-6B** with a 128k context window|
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![](assets/leaderboard.png)
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## Model usage
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Chat prompt template for LongAlign-6B-64k:
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```text
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[Round 1]
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问:Hi!
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答:Hello! What can I assist you today?
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[Round 2]
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问:What should I do if I can't sleep at night?
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答:
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```
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Chat prompt template for LongAlign-7B-64k and LongAlign-13B-64k:
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```text
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[INST]Hi![/INST]Hello! What can I assist you today?
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[INST]What should I do if I can't sleep at night?[/INST]
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```
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ChatGLM3-6B-128k uses the same prompt template as [ChatGLM3-6B](https://huggingface.co/THUDM/chatglm3-6b).
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A simple demo for deployment of the model:
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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tokenizer = AutoTokenizer.from_pretrained("THUDM/LongAlign-6B-64k", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("THUDM/LongAlign-6B-64k", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
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model = model.eval()
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query = open("assets/paper.txt").read() + "\n\nPlease summarize the paper."
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response, history = model.chat(tokenizer, query, history=[], max_new_tokens=512, temperature=1)
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print(response)
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```
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## Citation
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If you find our work useful, please consider citing LongAlign:
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```
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```
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assets/leaderboard.png
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config.json
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{
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"_name_or_path": "/mnt/vepfs/users/bys/fix_models/Llama-2-13b-64k-LongAlign-sort",
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"architectures": [
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"LlamaModel"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 13824,
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"max_position_embeddings": 65536,
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"max_sequence_length": 65536,
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"model_type": "llama",
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"num_attention_heads": 40,
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"num_hidden_layers": 40,
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"num_key_value_heads": 40,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 2000000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.33.0",
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"use_cache": true,
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"vocab_size": 32256
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}
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generation_config.json
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{
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"bos_token_id": 1,
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"eos_token_id": 2,
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"max_length": 65536,
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"pad_token_id": 0,
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"temperature": 0.9,
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"top_p": 0.6,
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"transformers_version": "4.31.0"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:192bbd9ab547444d92487acac6f0e102eecdd4ba0a9b81d11f2d7d57dcb673c5
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size 26037067133
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special_tokens_map.json
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{
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"content": "<s>",
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"lstrip": false,
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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size 499723
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tokenizer_config.json
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{
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"add_bos_token": true,
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"padding_side": "right",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<unk>",
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