Instructions to use Saddammm/T5Model100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saddammm/T5Model100 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Saddammm/T5Model100") model = AutoModelForSeq2SeqLM.from_pretrained("Saddammm/T5Model100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Saddammm/T5Model100: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/Saddammm/T5Model100/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Saddammm/T5Model100/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Saddammm/T5Model100/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- eaafed6200a24b8aa0e03f636c2ef47c1a351b9b27689e2c24116be89849592c
- Size of remote file:
- 990 MB
- SHA256:
- e5d24282d7b4e9fb86b0fc76b3ff7d6b3290e0169dd2f7290fdf5227d46200f8
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