Transformers
PyTorch
English
t5
text2text-generation
semantic-role-labeling
question-answer generation
text-generation-inference
Instructions to use kleinay/qanom-seq2seq-model-joint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kleinay/qanom-seq2seq-model-joint with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kleinay/qanom-seq2seq-model-joint") model = AutoModelForSeq2SeqLM.from_pretrained("kleinay/qanom-seq2seq-model-joint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 710a0bc681e9c046e09695bece2aba95776543e26ded6f9fbdbf32e0818a87f8
- Size of remote file:
- 242 MB
- SHA256:
- 67987af0aa8b7d2584e73cfaa33571bae84c52e4bc3534c5e896e1e7824343bd
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