Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ett1112/amazon_sentiment_sample_of_1900 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ett1112/amazon_sentiment_sample_of_1900 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ett1112/amazon_sentiment_sample_of_1900")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ett1112/amazon_sentiment_sample_of_1900") model = AutoModelForSequenceClassification.from_pretrained("ett1112/amazon_sentiment_sample_of_1900", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 279c94202054cd791b502e3405ab0847cb62f09e01d4f389d51046188f58a5b8
- Size of remote file:
- 3.25 kB
- SHA256:
- 8a92a8dff40407c88f7c0d769b9a3084897a7a6496d8fb30332dbbbab11c8a4a
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