Instructions to use Rostlab/ProstT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rostlab/ProstT5 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" 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("translation", model="Rostlab/ProstT5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Rostlab/ProstT5") model = AutoModelForSeq2SeqLM.from_pretrained("Rostlab/ProstT5") - Notebooks
- Google Colab
- Kaggle
Updated README.md to fix minor errors and update to be in line with new huggingface v5
#4
by AeneasTews - opened
Updated README.md to be in line with huggingface v5: https://github.com/huggingface/transformers/releases/tag/v5.0.0
Also fixed minor syntactic error:
tokenizer.batch_encode_plus(sequences_example, ...
min_len = min([ len(s) for s in folding_example])
max_len = max([ len(s) for s in folding_example])
etc.