Text Classification
Transformers
PyTorch
English
bert
sentiment
sentiment-analysis
text-embeddings-inference
Instructions to use MarieAngeA13/Sentiment-Analysis-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarieAngeA13/Sentiment-Analysis-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarieAngeA13/Sentiment-Analysis-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarieAngeA13/Sentiment-Analysis-BERT") model = AutoModelForSequenceClassification.from_pretrained("MarieAngeA13/Sentiment-Analysis-BERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
938fb42
1
Parent(s): f62d3f1
Update config.json
Browse files- config.json +1 -1
config.json
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.30.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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