Instructions to use Wimflorijn/t5-pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wimflorijn/t5-pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Wimflorijn/t5-pretrained")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Wimflorijn/t5-pretrained") model = AutoModel.from_pretrained("Wimflorijn/t5-pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fb8c8b774b652b3d65c39665d60b908ee16a2c8cbabed45bd3b117c0607dd1b8
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size 192482728
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