Text Classification
Transformers
PyTorch
TensorBoard
data2vec-text
Generated from Trainer
Eval Results (legacy)
Instructions to use mrm8488/data2vec-text-base-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/data2vec-text-base-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/data2vec-text-base-finetuned-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/data2vec-text-base-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/data2vec-text-base-finetuned-mrpc") - Notebooks
- Google Colab
- Kaggle
Align label mapping with mrpc config of glue dataset
#1
by lewtun HF Staff - opened
- config.json +10 -2
config.json
CHANGED
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@@ -26,5 +26,13 @@
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"transformers_version": "4.18.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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"transformers_version": "4.18.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265,
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"label2id": {
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"not_equivalent": 0,
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"equivalent": 1
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},
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"id2label": {
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"0": "not_equivalent",
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"1": "equivalent"
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}
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}
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