Summarization
Transformers
PyTorch
TensorFlow
TensorBoard
mt5
text2text-generation
Generated from Trainer
Instructions to use huggingface-course/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 huggingface-course/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="huggingface-course/mt5-small-finetuned-amazon-en-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("huggingface-course/mt5-small-finetuned-amazon-en-es") model = AutoModelForSeq2SeqLM.from_pretrained("huggingface-course/mt5-small-finetuned-amazon-en-es") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files
config.json
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 250112
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}
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.12.0.dev0",
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"use_cache": true,
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"vocab_size": 250112
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}
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pytorch_model.bin
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runs/Oct06_09-16-36_vorace/1633504871.3913915/events.out.tfevents.1633504871.vorace.3479400.1
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runs/Oct06_09-16-36_vorace/events.out.tfevents.1633504866.vorace.3479400.0
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training_args.bin
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size 2991
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