Instructions to use lysandre/dum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lysandre/dum with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lysandre/dum")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lysandre/dum") model = AutoModelForSequenceClassification.from_pretrained("lysandre/dum") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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"id2label": {
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"0": "NEGATIVE",
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"1": "POSITIVE"
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}
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"label2id": {
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"NEGATIVE": 0,
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"POSITIVE": 1
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"id2label": {
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"0": "NEGATIVE",
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"1": "POSITIVE"
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},
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"label2id": {
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"NEGATIVE": 0,
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"POSITIVE": 1
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