Instructions to use Hansollll/translation_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hansollll/translation_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Hansollll/translation_model") model = AutoModelForSeq2SeqLM.from_pretrained("Hansollll/translation_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Hansollll/translation_model: direct link, hf CLI and curl.
- Browser
- Download file 310 MB
-
https://huggingface.co/Hansollll/translation_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Hansollll/translation_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Hansollll/translation_model/resolve/main/pytorch_model.bin
310 MB
- Xet hash:
- 0351558071d824d5ba3729f32d745bec165fa7058a69326754d61c1e33140244
- Size of remote file:
- 310 MB
- SHA256:
- 36256457e9b1441cb87221d11745b872ba60802bbda917c7f5743a24b62d7e8c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.