Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use gcapde/gcapde-finetuned-amazon_reviews_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gcapde/gcapde-finetuned-amazon_reviews_multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gcapde/gcapde-finetuned-amazon_reviews_multi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gcapde/gcapde-finetuned-amazon_reviews_multi") model = AutoModelForSequenceClassification.from_pretrained("gcapde/gcapde-finetuned-amazon_reviews_multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gcapde/gcapde-finetuned-amazon_reviews_multi: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/gcapde/gcapde-finetuned-amazon_reviews_multi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gcapde/gcapde-finetuned-amazon_reviews_multi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gcapde/gcapde-finetuned-amazon_reviews_multi/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 7ee4297ffbc331b757e8caf16e703e484987a957a0273fe500cfde4c6377daf1
- Size of remote file:
- 499 MB
- SHA256:
- ce3f2ef6243faf3e637cee8b6d43932ba6b07a93e2f18030a645ee11abb8bb0e
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