Instructions to use Jeevesh8/t5-small_re-cogs_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/t5-small_re-cogs_7 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/t5-small_re-cogs_7") model = AutoModelForSeq2SeqLM.from_pretrained("Jeevesh8/t5-small_re-cogs_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Jeevesh8/t5-small_re-cogs_7: direct link, hf CLI and curl.
- Browser
- Download file 308 MB
-
https://huggingface.co/Jeevesh8/t5-small_re-cogs_7/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Jeevesh8/t5-small_re-cogs_7/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Jeevesh8/t5-small_re-cogs_7/resolve/main/flax_model.msgpack
308 MB
- Xet hash:
- e9efc1ac10db6b5a7d3298d572ed2e5220aee5c2e33d7a76bac189bf94038ad2
- Size of remote file:
- 308 MB
- SHA256:
- 15813d111ed56e5622b6e46ea6676187ba409a0563992f6a4687d6c400035592
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