Instructions to use AlienKevin/bart-canto-mando-base-bitext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlienKevin/bart-canto-mando-base-bitext with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="AlienKevin/bart-canto-mando-base-bitext")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlienKevin/bart-canto-mando-base-bitext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-6000/optimizer.pt from AlienKevin/bart-canto-mando-base-bitext: direct link, hf CLI and curl.
- Browser
- Download file 878 MB
-
https://huggingface.co/AlienKevin/bart-canto-mando-base-bitext/resolve/main/checkpoint-6000/optimizer.pt
- Command line
-
hf download hf://AlienKevin/bart-canto-mando-base-bitext/checkpoint-6000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/AlienKevin/bart-canto-mando-base-bitext/resolve/main/checkpoint-6000/optimizer.pt
878 MB
- Xet hash:
- 360acf91817df342fe45c88d22db8de03f75d1061038b5bc0051b003cb1d0913
- Size of remote file:
- 878 MB
- SHA256:
- 6504aa9624490dbd0cde66fc5951db06b3ab024e87d7cbba765b2c428c629ad2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.