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 flax_model.msgpack 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/flax_model.msgpack
- Command line
-
hf download hf://Rostlab/prot_t5_base_mt_uniref50/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Rostlab/prot_t5_base_mt_uniref50/resolve/main/flax_model.msgpack
795 MB
- Xet hash:
- a63bd0c1877b6d85f2e5867e9067c09fe1bf3f54bc4e7a14fb478d3e0577ae0b
- Size of remote file:
- 795 MB
- SHA256:
- 6cc6815c6e22863a1764a8a442b9686a3772cc1fcead2ac5c7c587855252776d
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