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 pytorch_model.bin from bweb771/deberta_amazon_reviews_v1: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/bweb771/deberta_amazon_reviews_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bweb771/deberta_amazon_reviews_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bweb771/deberta_amazon_reviews_v1/resolve/main/pytorch_model.bin
738 MB
- Xet hash:
- b4804704e00be76065068ce9cbae2151c82356b68c5ba20bc69fcbb0d04bb1e2
- Size of remote file:
- 738 MB
- SHA256:
- 61ab0d0eac2e9f34b71296631943eef5dbe6e2e4259a9f353da18ba0122f2a54
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