👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
APACHE-2.0 License
**** | English
PaddleNLP(LLM)PaddleNLP ********
**2024.08.08 PaddleNLP 3.0 **8221900https://www.wjx.top/vm/Y2f7FFY.aspx?udsid=143844
**2024.06.27 PaddleNLP v3.0 Beta**4D RsLoRA+ Unified Checkpoint FastFFNFusedQKV
2024.04.24 PaddleNLP v2.8 RsLoRA+ PEFT RLHF PPO PPO PPO FastFFNFusedQKV
4D Trainer Unified Checkpoint
FlashMask
LLaMA | facebook/llama-7b, facebook/llama-13b, facebook/llama-30b, facebook/llama-65b |
LLama2 | meta-llama/Llama-2-7b, meta-llama/Llama-2-7b-chat, meta-llama/Llama-2-13b, meta-llama/Llama-2-13b-chat, meta-llama/Llama-2-70b, meta-llama/Llama-2-70b-chat |
LLama3 | meta-llama/Meta-Llama-3-8B, meta-llama/Meta-Llama-3-8B-Instruct, meta-llama/Meta-Llama-3-70B, meta-llama/Meta-Llama-3-70B-Instruct |
LLama3.1 | meta-llama/Meta-Llama-3.1-8B, meta-llama/Meta-Llama-3.1-8B-Instruct, meta-llama/Meta-Llama-3.1-70B, meta-llama/Meta-Llama-3.1-70B-Instruct, meta-llama/Meta-Llama-3.1-405B, meta-llama/Meta-Llama-3.1-405B-Instruct, meta-llama/Llama-Guard-3-8B |
LLama3.2 | meta-llama/Llama-3.2-1B, meta-llama/Llama-3.2-1B-Instruct, meta-llama/Llama-3.2-3B, meta-llama/Llama-3.2-3B-Instruct, meta-llama/Llama-Guard-3-1B |
Baichuan | baichuan-inc/Baichuan-7B, baichuan-inc/Baichuan-13B-Base, baichuan-inc/Baichuan-13B-Chat |
Baichuan2 | baichuan-inc/Baichuan2-7B-Base, baichuan-inc/Baichuan2-7B-Chat, baichuan-inc/Baichuan2-13B-Base, baichuan-inc/Baichuan2-13B-Chat |
Bloom | bigscience/bloom-560m, bigscience/bloom-560m-bf16, bigscience/bloom-1b1, bigscience/bloom-3b, bigscience/bloom-7b1, bigscience/bloomz-560m, bigscience/bloomz-1b1, bigscience/bloomz-3b, bigscience/bloomz-7b1-mt, bigscience/bloomz-7b1-p3, bigscience/bloomz-7b1, bellegroup/belle-7b-2m |
ChatGLM | THUDM/chatglm-6b, THUDM/chatglm-6b-v1.1 |
ChatGLM2 | THUDM/chatglm2-6b |
ChatGLM3 | THUDM/chatglm3-6b |
Gemma | google/gemma-7b, google/gemma-7b-it, google/gemma-2b, google/gemma-2b-it |
Mistral | mistralai/Mistral-7B-Instruct-v0.3, mistralai/Mistral-7B-v0.1 |
Mixtral | mistralai/Mixtral-8x7B-Instruct-v0.1 |
OPT | facebook/opt-125m, facebook/opt-350m, facebook/opt-1.3b, facebook/opt-2.7b, facebook/opt-6.7b, facebook/opt-13b, facebook/opt-30b, facebook/opt-66b, facebook/opt-iml-1.3b, opt-iml-max-1.3b |
Qwen | qwen/qwen-7b, qwen/qwen-7b-chat, qwen/qwen-14b, qwen/qwen-14b-chat, qwen/qwen-72b, qwen/qwen-72b-chat, |
Qwen1.5 | Qwen/Qwen1.5-0.5B, Qwen/Qwen1.5-0.5B-Chat, Qwen/Qwen1.5-1.8B, Qwen/Qwen1.5-1.8B-Chat, Qwen/Qwen1.5-4B, Qwen/Qwen1.5-4B-Chat, Qwen/Qwen1.5-7B, Qwen/Qwen1.5-7B-Chat, Qwen/Qwen1.5-14B, Qwen/Qwen1.5-14B-Chat, Qwen/Qwen1.5-32B, Qwen/Qwen1.5-32B-Chat, Qwen/Qwen1.5-72B, Qwen/Qwen1.5-72B-Chat, Qwen/Qwen1.5-110B, Qwen/Qwen1.5-110B-Chat, Qwen/Qwen1.5-MoE-A2.7B, Qwen/Qwen1.5-MoE-A2.7B-Chat |
Qwen2 | Qwen/Qwen2-0.5B, Qwen/Qwen2-0.5B-Instruct, Qwen/Qwen2-1.5B, Qwen/Qwen2-1.5B-Instruct, Qwen/Qwen2-7B, Qwen/Qwen2-7B-Instruct, Qwen/Qwen2-72B, Qwen/Qwen2-72B-Instruct, Qwen/Qwen2-57B-A14B, Qwen/Qwen2-57B-A14B-Instruct |
Qwen2-Math | Qwen/Qwen2-Math-1.5B, Qwen/Qwen2-Math-1.5B-Instruct, Qwen/Qwen2-Math-7B, Qwen/Qwen2-Math-7B-Instruct, Qwen/Qwen2-Math-72B, Qwen/Qwen2-Math-72B-Instruct, Qwen/Qwen2-Math-RM-72B |
Qwen2.5 | Qwen/Qwen2.5-0.5B, Qwen/Qwen2.5-0.5B-Instruct, Qwen/Qwen2.5-1.5B, Qwen/Qwen2.5-1.5B-Instruct, Qwen/Qwen2.5-3B, Qwen/Qwen2.5-3B-Instruct, Qwen/Qwen2.5-7B, Qwen/Qwen2.5-7B-Instruct, Qwen/Qwen2.5-14B, Qwen/Qwen2.5-14B-Instruct, Qwen/Qwen2.5-32B, Qwen/Qwen2.5-32B-Instruct, Qwen/Qwen2.5-72B, Qwen/Qwen2.5-72B-Instruct |
Qwen2.5-Math | Qwen/Qwen2.5-Math-1.5B, Qwen/Qwen2.5-Math-1.5B-Instruct, Qwen/Qwen2.5-Math-7B, Qwen/Qwen2.5-Math-7B-Instruct, Qwen/Qwen2.5-Math-72B, Qwen/Qwen2.5-Math-72B-Instruct, Qwen/Qwen2.5-Math-RM-72B |
Qwen2.5-Coder | Qwen/Qwen2.5-Coder-1.5B, Qwen/Qwen2.5-Coder-1.5B-Instruct, Qwen/Qwen2.5-Coder-7B, Qwen/Qwen2.5-Coder-7B-Instruct |
Yuan2 | IEITYuan/Yuan2-2B, IEITYuan/Yuan2-51B, IEITYuan/Yuan2-102B |
/ | |||||||
---|---|---|---|---|---|---|---|
stage1 | stage2 | stage3 | |||||
Llama | |||||||
Qwen | |||||||
Qwen1.5 | |||||||
Qwen2 | |||||||
Mixtral(moe) | |||||||
Mistral | |||||||
Baichuan | |||||||
Baichuan2 | |||||||
ChatGLM | |||||||
ChatGLM2 | |||||||
ChatGLM3 | |||||||
Bloom | |||||||
GPT-2/GPT-3 | |||||||
OPT | |||||||
Gemma | |||||||
Yuan2 |
/ | Pretrain | SFT | LoRA | Prefix Tuning | DPO | RLHF | Quantization | Torch convert |
---|---|---|---|---|---|---|---|---|
Llama | ||||||||
Qwen | ||||||||
Mixtral | ||||||||
Mistral | ||||||||
Baichuan/Baichuan2 | ||||||||
ChatGLM-6B | ||||||||
ChatGLM2/ChatGLM3 | ||||||||
Bloom | ||||||||
GPT-3 | ||||||||
OPT | ||||||||
Yuan2 |
/ | FP16/BF16 | WINT8 | WINT4 | INT8-A8W8 | FP8-A8W8 | INT8-A8W8C8 |
---|---|---|---|---|---|---|
LLaMA | ||||||
Qwen | ||||||
Qwen-Moe | ||||||
Mixtral | ||||||
ChatGLM | ||||||
Bloom | ||||||
BaiChuan |
pip install --upgrade paddlenlp==3.0.0b2
develop
pip install --pre --upgrade paddlenlp -f https://www.paddlepaddle.org.cn/whl/paddlenlp.html
PaddlePaddle PaddleNLP Installation
PaddleNLP Auto API Tokenizer Qwen/Qwen2-0.5B
>>> from paddlenlp.transformers import AutoTokenizer, AutoModelForCausalLM
>>> tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B")
>>> model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B", dtype="float16")
>>> input_features = tokenizer("", return_tensors="pd")
>>> outputs = model.generate(**input_features, max_length=128)
>>> print(tokenizer.batch_decode(outputs[0], skip_special_tokens=True))
['AI']
git clone https://github.com/PaddlePaddle/PaddleNLP.git && cd PaddleNLP # clonePaddleNLP
mkdir -p llm/data && cd llm/data
wget https://bj.bcebos.com/paddlenlp/models/transformers/llama/data/llama_openwebtext_100k.bin
wget https://bj.bcebos.com/paddlenlp/models/transformers/llama/data/llama_openwebtext_100k.idx
cd .. # change folder to PaddleNLP/llm
python -u -m paddle.distributed.launch --gpus "0,1,2,3,4,5,6,7" run_pretrain.py ./config/llama/pretrain_argument.json
git clone https://github.com/PaddlePaddle/PaddleNLP.git && cd PaddleNLP # clonePaddleNLP
mkdir -p llm/data && cd llm/data
wget https://bj.bcebos.com/paddlenlp/datasets/examples/AdvertiseGen.tar.gz && tar -zxvf AdvertiseGen.tar.gz
cd .. # change folder to PaddleNLP/llm
python -u -m paddle.distributed.launch --gpus "0,1,2,3,4,5,6,7" run_finetune.py ./config/llama/sft_argument.json
PaddleNLP
PaddleNLP
@misc{=paddlenlp,
title={PaddleNLP: An Easy-to-use and High Performance NLP Library},
author={PaddleNLP Contributors},
howpublished = {\url{https://github.com/PaddlePaddle/PaddleNLP}},
year={2021}
}
Hugging Face Transformers Hugging Face
PaddleNLP Apache-2.0