Instructions to use castorini/afriteva_v2_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/afriteva_v2_large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("castorini/afriteva_v2_large") model = AutoModelForSeq2SeqLM.from_pretrained("castorini/afriteva_v2_large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from castorini/afriteva_v2_large: direct link, hf CLI and curl.
- Browser
- Download file 4.1 GB
-
https://huggingface.co/castorini/afriteva_v2_large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://castorini/afriteva_v2_large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/castorini/afriteva_v2_large/resolve/main/pytorch_model.bin
4.1 GB
- Xet hash:
- 5bbd16ee0632ec5bac99e6224f2d0f626b1a33419e1745d72dfc9b813d2631de
- Size of remote file:
- 4.1 GB
- SHA256:
- 7e8945c19d7caf930bb0877f6be505b38dacd6a0a928c374a24965ca58e08798
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.