Instructions to use mapra2025/msa_prot_t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mapra2025/msa_prot_t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mapra2025/msa_prot_t5") model = AutoModelForSeq2SeqLM.from_pretrained("mapra2025/msa_prot_t5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 018c7e568e598e0cfe407489cbedd2f3ebe726099ebd3bdc65a5a4a9b74db755
- Size of remote file:
- 5.78 kB
- SHA256:
- fb2f9f5a08f24034122e21db9b9834e648ad6e56a3c8d9c1ec09c230bb76b7d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.