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 optimizer.pt from Saddammm/T5Model100: direct link, hf CLI and curl.
- Browser
- Download file 1.98 GB
-
https://huggingface.co/Saddammm/T5Model100/resolve/main/optimizer.pt
- Command line
-
hf download hf://Saddammm/T5Model100/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Saddammm/T5Model100/resolve/main/optimizer.pt
1.98 GB
- Xet hash:
- 107edfcacfe1697ba59bb14bdc588d446ec73a5fc6e39ee8d7d6d1327e43fec4
- Size of remote file:
- 1.98 GB
- SHA256:
- 8eda2d9b4aeed2e5d31f9e0b355450ad224a0c3f8a88f5d74d841f1825d6e7bb
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