Instructions to use DAMO-NLP-SG/rememo-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/rememo-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, T5ForTemporalPretraining tokenizer = AutoTokenizer.from_pretrained("DAMO-NLP-SG/rememo-base") model = T5ForTemporalPretraining.from_pretrained("DAMO-NLP-SG/rememo-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from DAMO-NLP-SG/rememo-base: direct link, hf CLI and curl.
- Browser
- Download file 1,000 MB
-
https://huggingface.co/DAMO-NLP-SG/rememo-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DAMO-NLP-SG/rememo-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DAMO-NLP-SG/rememo-base/resolve/main/pytorch_model.bin
1,000 MB
- Xet hash:
- 83da0e87168805395aeb687927b11fc5bfbdc7a61feb61516e35c65ac334bf9c
- Size of remote file:
- 1,000 MB
- SHA256:
- 5d19b4834628ab4298d89e7fce1ad1ff754624d06f87e0ac07f98059d20ca07b
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