Instructions to use Jeevesh8/t5-small_re-cogs_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/t5-small_re-cogs_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/t5-small_re-cogs_2") model = AutoModelForSeq2SeqLM.from_pretrained("Jeevesh8/t5-small_re-cogs_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Jeevesh8/t5-small_re-cogs_2: direct link, hf CLI and curl.
- Browser
- Download file 308 MB
-
https://huggingface.co/Jeevesh8/t5-small_re-cogs_2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Jeevesh8/t5-small_re-cogs_2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Jeevesh8/t5-small_re-cogs_2/resolve/main/flax_model.msgpack
308 MB
- Xet hash:
- 3da5d54907709eb77b50ce3f436f6a3f658329969de172b865e33eafdb1cecb3
- Size of remote file:
- 308 MB
- SHA256:
- dd04965bb1f9981f4453babc4d072a520fe8160b01e2b8ec93d8ab022c6e4a36
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