Instructions to use MadMarx37/mt5-small-finetuned-amazon-en-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MadMarx37/mt5-small-finetuned-amazon-en-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="MadMarx37/mt5-small-finetuned-amazon-en-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MadMarx37/mt5-small-finetuned-amazon-en-es") model = AutoModelForSeq2SeqLM.from_pretrained("MadMarx37/mt5-small-finetuned-amazon-en-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a39fc7cc9fa07a2000edfb6f0d5d52562f760e23fc530da9a345e8b496e5495f
- Size of remote file:
- 16.3 MB
- SHA256:
- cd38144ed4e51886247b55a7fd9b6fcca7afd7355345b522149ba074b455f2cb
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