wac81/toy_retnet_1.3b_pretrain

介绍 (Introduction)

retnet-1.3B-toy 是一个开源模型。主要是为探索模型小型化，测试小数据量训练的最佳效果。

1. 根据retnet论文(https://arxiv.org/pdf/2307.08621.pdf)开发并基于transformer文本生成模型。该仓库的算法实现根据repo进行(https://github.com/syncdoth/RetNet.git)
2. 该仓库目标是建立一个retnet基础训练仓库，建议做学习研究使用，不建议商用。
3. 该仓库只使用wiki文本和少量sharegpt/belle/多轮指令数据集训练而成。包含中英文数据，数据估算占比7:3。
4. 本次放出pretrain模型与sft微调后模型。
5. 本模型使用了tokenizer为百川大模型的第一版分词器，共包含64000个vocab。
6. 已知问题：

• 会出现重复句子回答，可以调节topk减轻该问题。
• 会出现回答不全问题，可以提高max_new_token缓解该问题。
• 由于知识储备不足，回答准确性一般。

retnet-1.3B-toy is an open source model.

1. Developed according to retnet paper (https://arxiv.org/pdf/2307.08621.pdf) and based on transformer text generation model. The algorithmic implementation of this repository is carried out according to repo (https://github.com/syncdoth/RetNet.git)
2. The goal of this repository is to suggest a retnet base training repository, which is recommended to be used for learning research and not for commercial use.
3. This repository is trained using only wiki text and a small amount of sharegpt/belle instruction dataset.
4. This release pretrain model with sft fine-tuned model.
5. This model uses the tokenizer as the first version of the BaiChuan model tokenizer, which contains a total of 64,000 vocabs.
6. known issues:

• Repeated sentence answers will occur, topk can be adjusted to mitigate the problem.
• Incomplete answers will occur, you can increase max_new_token to alleviate the problem.
• Answer accuracy is average due to insufficient knowledge base.

软件依赖 (Dependencies)

pip install torch transformers

模型&代码仓库（Model&Code Repo）

1. 基础预训练模型(pretrain model) (https://huggingface.co/wac81/toy_retnet_1.3b_pretrain)
2. sft微调后模型(sft model) (https://huggingface.co/wac81/toy_retnet_1.3b)
3. Code Repo (https://github.com/wac81/toy_retnet_1.3b)

最小需求 (Minimum Requirements)

模型可以完全加载在8GB显卡上，8bit/4bit量化后，理论上可以加载在4GB显卡上

The model can be fully loaded on an 8GB graphics card, and after 8bit or 4bit quantization, it can theoretically be loaded on a 4GB graphics card

代码调用 (Code Usage)

sft模型下载后放入checkpoints/checkpoint-21000目录，可以通过如下代码调用 retnet-1.3B-toy 模型来生成对话：

After the sft model is downloaded and put into the checkpoints/checkpoint-21000 directory, you can call the retnet-1.3B-toy model to generate a dialog with the following code:

python generate.py

user:中医如何医治风寒
system:中医的治疗方法主要包括针灸、针灸、推拿、太极拳等。针灸可以帮助人体解毒、调节身体温度，针灸可以刺激人体的血液循环，推拿可以促进血液循环，推拿可以促进血液循环，从而缓解身体不适。针灸可以帮助人体解毒、调节身体温度，推拿可以促进血液循环，从而缓解身体不适。太极拳则可以帮助人体解毒、调节身体温度，推拿可以促进血液循环，从而缓解身体不适。太极拳则可以帮助人体解毒、调节身体温度，推拿可以促进血液循环，

协议 (License)

本仓库的代码依照 Apache-2.0 协议开源，retnet-1.3B-toy 模型的权重的使用则需要遵循 Model License。

The code in this repository is open-sourced under the Apache-2.0 license, while the use of the retnet-1.3B-toy model weights needs to comply with the Model License.