Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use bweb771/deberta_amazon_reviews_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bweb771/deberta_amazon_reviews_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bweb771/deberta_amazon_reviews_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bweb771/deberta_amazon_reviews_v1") model = AutoModelForSequenceClassification.from_pretrained("bweb771/deberta_amazon_reviews_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bweb771/deberta_amazon_reviews_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/bweb771/deberta_amazon_reviews_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://bweb771/deberta_amazon_reviews_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bweb771/deberta_amazon_reviews_v1/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 0d3e263640d3839d7f1f169861b2b6547ca043e18ea99d404bbaeb44fcff69bb
- Size of remote file:
- 3.39 kB
- SHA256:
- 70971fae3dbc86f63d5b95f35019a20d8b47a214d7fd63a323f098e073112d96
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