Instructions to use Rostlab/prot_t5_base_mt_uniref50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rostlab/prot_t5_base_mt_uniref50 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="Rostlab/prot_t5_base_mt_uniref50")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("Rostlab/prot_t5_base_mt_uniref50") model = AutoModelWithLMHead.from_pretrained("Rostlab/prot_t5_base_mt_uniref50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Rostlab/prot_t5_base_mt_uniref50: direct link, hf CLI and curl.
- Browser
- Download file 795 MB
-
https://huggingface.co/Rostlab/prot_t5_base_mt_uniref50/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Rostlab/prot_t5_base_mt_uniref50/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Rostlab/prot_t5_base_mt_uniref50/resolve/main/pytorch_model.bin
795 MB
- Xet hash:
- 1141c798aaac9e53e36e5273c5995041c35360279e4f8f63a4c7c6d4753e6f20
- Size of remote file:
- 795 MB
- SHA256:
- 59f087fc34346574074969e62abb9285950ca1dd5ae08e1493bed0ad00f49631
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