license: mit
datasets:
- p208p2002/wudao
language:
- zh
Chinese TinyLlama
A demo project that pretrains a tinyllama on Chinese corpora, with minimal modification to the huggingface transformers code. It serves as a use case to demonstrate how to use the huggingface version TinyLlama to pretrain a model on a large corpus.
See the Github Repo for more details.
Usage
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("whynlp/tinyllama-zh", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("whynlp/tinyllama-zh")
Model Details
Model Description
This model is trained on WuDaoCorpora Text. The dataset contains about 45B tokens and the model is trained for 2 epochs. The training takes about 6 days on 8 A100 GPUs.
The model uses the THUDM/chatglm3-6b tokenizer from huggingface.
- Model type: Llama
- Language(s) (NLP): Chinese
- License: MIT
- Finetuned from model [optional]: TinyLlama-2.5T checkpoint
Uses
The model does not perform very well (The CMMLU result is slightly above 25). For better performance, one may use a better corpus (e.g. wanjuan). Again, this project only serves as a demonstration of how to pretrain a TinyLlama on a large corpus.