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 flax_model.msgpack 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/flax_model.msgpack
- Command line
-
hf download hf://castorini/afriteva_v2_large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/castorini/afriteva_v2_large/resolve/main/flax_model.msgpack
4.1 GB
- Xet hash:
- 951b1f6a4556fc71c60a6d75f48dfb00960702dfb7cef7be4f4ba340e378e434
- Size of remote file:
- 4.1 GB
- SHA256:
- 8ea8d7a220ed8a3c6ee7ad38ceaa8d292ae0057782d652d200bb1e6e5504c185
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