Instructions to use ELiRF/mt5-base-dacsa-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ELiRF/mt5-base-dacsa-es with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="ELiRF/mt5-base-dacsa-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ELiRF/mt5-base-dacsa-es") model = AutoModelForSeq2SeqLM.from_pretrained("ELiRF/mt5-base-dacsa-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12acdf4394ee8684d24c90c090d5d01a3a45942f93c84930c888b80ae4e34826
- Size of remote file:
- 2.33 GB
- SHA256:
- 1ae2bc3d21b1a270f3dd6452cd0a6b99a5fa62ac21b3b4ea08d47c38cd7e6b58
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