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/e185432f866d04f552fa0386293cbdb5ca81ced2/pytorch_model.bin
- Command line
-
hf download hf://Python-proje/mymodel@e185432f866d04f552fa0386293cbdb5ca81ced2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Python-proje/mymodel/resolve/e185432f866d04f552fa0386293cbdb5ca81ced2/pytorch_model.bin
558 MB
- Xet hash:
- e5277a7d3f35519cad406291ca02a65c0a55b4aa7ac5d952ace71c1c6a39b10c
- Size of remote file:
- 558 MB
- SHA256:
- 54ffde5b137421695c175fc23b842aa77cbdf24606271cfb09b328aa0c9e97f8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.