Instructions to use RedBaron5/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedBaron5/content with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RedBaron5/content") model = AutoModelForSeq2SeqLM.from_pretrained("RedBaron5/content", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RedBaron5/content: direct link, hf CLI and curl.
- Browser
- Download file 648 MB
-
https://huggingface.co/RedBaron5/content/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RedBaron5/content/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RedBaron5/content/resolve/main/pytorch_model.bin
648 MB
- Xet hash:
- bb4bbac2330a67197882d156f37ae59b45efadb54b1ff65a936e9ff85b80fc17
- Size of remote file:
- 648 MB
- SHA256:
- 1bd02b93c0788b81133407c34c3d1a3e04de6b4f142aae1895bc48c467103802
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.