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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/tinybert-sentiment-amazon") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/tinybert-sentiment-amazon", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/model.onnx from AdamCodd/tinybert-sentiment-amazon: direct link, hf CLI and curl.
- Browser
- Download file 17.6 MB
-
https://huggingface.co/AdamCodd/tinybert-sentiment-amazon/resolve/main/onnx/model.onnx
- Command line
-
hf download hf://AdamCodd/tinybert-sentiment-amazon/onnx/model.onnx
-
curl -L -o model.onnx https://huggingface.co/AdamCodd/tinybert-sentiment-amazon/resolve/main/onnx/model.onnx
17.6 MB
- Xet hash:
- f3931cc3cd9ef1c7ca2356c16d6e2a8dfafa567d8fc4923f3c0f4b89678aa487
- Size of remote file:
- 17.6 MB
- SHA256:
- 6174486fc5e1f2f02e9722d219cdc45098ced06770fc8032dc9717b3e2fb6576
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