Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use dinhlnd1610/distilbert-base-uncased-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dinhlnd1610/distilbert-base-uncased-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dinhlnd1610/distilbert-base-uncased-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dinhlnd1610/distilbert-base-uncased-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("dinhlnd1610/distilbert-base-uncased-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
distilbert-base-uncased-finetuned-sst2 / runs /Dec06_08-42-17_486c67ed138d /events.out.tfevents.1701854088.486c67ed138d.2142.3
- Xet hash:
- 3accb995fd3e7393cd35fcbf101968f8a84e177cff3d5cc52ef87f3b7bba9c81
- Size of remote file:
- 12.9 kB
- SHA256:
- c3c232fa2780f03c6b9956aae4158f42aeaa4c9b3d258b1355c097d8f3736e85
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