Instructions to use casualprogrammer/shadow_mbart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use casualprogrammer/shadow_mbart with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/mbart-large-50") model = PeftModel.from_pretrained(base_model, "casualprogrammer/shadow_mbart") - Transformers
How to use casualprogrammer/shadow_mbart with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("casualprogrammer/shadow_mbart") model = AutoModelForSeq2SeqLM.from_pretrained("casualprogrammer/shadow_mbart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-15747/optimizer.pt from casualprogrammer/shadow_mbart: direct link, hf CLI and curl.
- Browser
- Download file 69.5 MB
-
https://huggingface.co/casualprogrammer/shadow_mbart/resolve/main/checkpoint-15747/optimizer.pt
- Command line
-
hf download hf://casualprogrammer/shadow_mbart/checkpoint-15747/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/casualprogrammer/shadow_mbart/resolve/main/checkpoint-15747/optimizer.pt
69.5 MB
- Xet hash:
- 99fbcac15b2bfaeb88b10254e088e9a2ad0039dc132ff6c3d582a06aecbf1dcf
- Size of remote file:
- 69.5 MB
- SHA256:
- 305ca4d383e476beef6df746808ae0814a697f6cab16044cb37e5ef5c5dc34bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.