Text Classification
Transformers
ONNX
Safetensors
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use AdamCodd/tinybert-sentiment-amazon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/tinybert-sentiment-amazon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/tinybert-sentiment-amazon")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/tinybert-sentiment-amazon") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/tinybert-sentiment-amazon") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a76ea8938d7febd1451a4fad43db40e329356093e0a5150e4644887424d00de3
- Size of remote file:
- 17.5 MB
- SHA256:
- b2a21c60684abaf7d56ee423b70f24c8830435ef7e28f1eeee1c735a53b7a9c1
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