Instructions to use el-profesor/bert_small_seq2seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use el-profesor/bert_small_seq2seq with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("el-profesor/bert_small_seq2seq") model = AutoModelForSeq2SeqLM.from_pretrained("el-profesor/bert_small_seq2seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f3e66de8b5384a9c390c316a3281f6683d7aadc174d35925274ebee34047a67
- Size of remote file:
- 247 MB
- SHA256:
- abde29a9fe7f17f2c1cd0f5561c0ba903fb2745960e024ff14f562b1deae448a
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