Instructions to use wawaup/MengziT5-Comment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wawaup/MengziT5-Comment with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("wawaup/MengziT5-Comment") model = AutoModelForSeq2SeqLM.from_pretrained("wawaup/MengziT5-Comment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from wawaup/MengziT5-Comment: direct link, hf CLI and curl.
- Browser
- Download file 1.98 GB
-
https://huggingface.co/wawaup/MengziT5-Comment/resolve/main/optimizer.pt
- Command line
-
hf download hf://wawaup/MengziT5-Comment/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/wawaup/MengziT5-Comment/resolve/main/optimizer.pt
1.98 GB
- Xet hash:
- f299738944b0f84e59d92f16fa137bed944998eed5bfccbb3cff62c976ab62e7
- Size of remote file:
- 1.98 GB
- SHA256:
- 64050a7d3cca2e99eb1cebb9e8dd3b08d7e5635b8057a755ad031132ad1e754b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.