Instructions to use Akul/t5-small-command-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akul/t5-small-command-extractor with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Akul/t5-small-command-extractor") model = AutoModelForSeq2SeqLM.from_pretrained("Akul/t5-small-command-extractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d86f47a5b08cc4ab3158d8c0044aa9927102a50d4abb40d22dbe4312e76c47cb
- Size of remote file:
- 374 MB
- SHA256:
- b09a9ab90c1ba9a0ae90162fbf18fd286e33fc242759fb63eb2a2972cc545406
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