Instructions to use Jeevesh8/t5-small_re-cogs_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/t5-small_re-cogs_3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/t5-small_re-cogs_3") model = AutoModelForSeq2SeqLM.from_pretrained("Jeevesh8/t5-small_re-cogs_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Jeevesh8/t5-small_re-cogs_3: direct link, hf CLI and curl.
- Browser
- Download file 308 MB
-
https://huggingface.co/Jeevesh8/t5-small_re-cogs_3/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Jeevesh8/t5-small_re-cogs_3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Jeevesh8/t5-small_re-cogs_3/resolve/main/flax_model.msgpack
308 MB
- Xet hash:
- bced48b251d95b02679991983147ceb0fe2638410a7be46923bf6096a8e94fb4
- Size of remote file:
- 308 MB
- SHA256:
- dbdf8aa304fcf51c570211ae1c081358143c4010e0e37a2d10ada8863c5878f7
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