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:
- d97328d6a212977b86ba182b65e623016fe306792da9bcabd81019d3b0eda1e6
- Size of remote file:
- 268 MB
- SHA256:
- 4253e14c544fa27e90ac49e9df21a9d5385f3268c79f7fb20cdc3f718fadadf6
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