Text Classification
Transformers
PyTorch
Catalan
roberta
catalan
paraphrase
textual entailment
Eval Results (legacy)
text-embeddings-inference
Instructions to use projecte-aina/roberta-large-ca-paraphrase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use projecte-aina/roberta-large-ca-paraphrase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="projecte-aina/roberta-large-ca-paraphrase")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-large-ca-paraphrase") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-large-ca-paraphrase") - Notebooks
- Google Colab
- Kaggle
Commit ·
fadf772
1
Parent(s): 7453d3b
Update config.json
Browse files- config.json +3 -3
config.json
CHANGED
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@@ -7,13 +7,13 @@
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"finetuning_task": "
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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0: "No Parafrasis",
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1: "Parafrasis"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"bos_token_id": 0,
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"classifier_dropout": null,
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| 9 |
"eos_token_id": 2,
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"finetuning_task": "text-classification",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "No Parafrasis",
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"1": "Parafrasis"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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