Instructions to use niuca/T5-learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niuca/T5-learning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("niuca/T5-learning") model = AutoModelForSeq2SeqLM.from_pretrained("niuca/T5-learning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from niuca/T5-learning: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/niuca/T5-learning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://niuca/T5-learning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/niuca/T5-learning/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- d686eca872dd60564dd55510ba6446c32ad9174ec51cd0dfeb2efff2b16190ff
- Size of remote file:
- 242 MB
- SHA256:
- f423061f5fd38d1b13ab17d5a59d1b7b62550c26de064e99b60d0ceffc8f4420
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