Instructions to use Medissa/t5_conetxt_first with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Medissa/t5_conetxt_first with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Medissa/t5_conetxt_first") model = AutoModelForSeq2SeqLM.from_pretrained("Medissa/t5_conetxt_first", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Medissa/t5_conetxt_first: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/Medissa/t5_conetxt_first/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Medissa/t5_conetxt_first/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Medissa/t5_conetxt_first/resolve/main/pytorch_model.bin
3.13 GB
- Xet hash:
- 998288bfa409dea4c578f7ec365e86447fbb51be008aca3c396f160a2cb81c68
- Size of remote file:
- 3.13 GB
- SHA256:
- 1c993ddb867ef6ad3a18be9a0366630bc83babedc46f79cb4389a8c48c83ac3a
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