Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jacobduncan00/hackMIT-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jacobduncan00/hackMIT-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jacobduncan00/hackMIT-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jacobduncan00/hackMIT-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("jacobduncan00/hackMIT-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
Align label mapping with sst2 config of glue dataset
#1
by lewtun HF Staff - opened
- config.json +10 -2
config.json
CHANGED
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@@ -22,5 +22,13 @@
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"transformers_version": "4.9.2",
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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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"transformers_version": "4.9.2",
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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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"label2id": {
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"negative": 0,
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"positive": 1
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},
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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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}
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