Instructions to use 51la5/distilbert-base-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 51la5/distilbert-base-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="51la5/distilbert-base-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("51la5/distilbert-base-sentiment") model = AutoModelForSequenceClassification.from_pretrained("51la5/distilbert-base-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76128442ff6415ba8783012c6ec1b3b0f5f4c59e4db5f738acf2e4c5a0691315
- Size of remote file:
- 268 MB
- SHA256:
- 60554cbd7781b09d87f1ececbea8c064b94e49a7f03fd88e8775bfe6cc3d9f88
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