Instructions to use Python-proje/mymodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Python-proje/mymodel with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Python-proje/mymodel") model = AutoModelForSeq2SeqLM.from_pretrained("Python-proje/mymodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Python-proje/mymodel: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/Python-proje/mymodel/resolve/e5987f1ef7634639d8609348189bdf83ea8eee31/pytorch_model.bin
- Command line
-
hf download hf://Python-proje/mymodel@e5987f1ef7634639d8609348189bdf83ea8eee31/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Python-proje/mymodel/resolve/e5987f1ef7634639d8609348189bdf83ea8eee31/pytorch_model.bin
558 MB
- Xet hash:
- 7f865d09d43608ab5bab364a3389ced453593546f4010d86d9512c9c72b7f7b2
- Size of remote file:
- 558 MB
- SHA256:
- adcb423c4d28cf7f0526ac9d8a08072c7b35bf518018142f3aad9435bcf59240
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.