Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use jialicheng/imdb_deberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jialicheng/imdb_deberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jialicheng/imdb_deberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jialicheng/imdb_deberta-base") model = AutoModelForSequenceClassification.from_pretrained("jialicheng/imdb_deberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jialicheng/imdb_deberta-base: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/jialicheng/imdb_deberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jialicheng/imdb_deberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jialicheng/imdb_deberta-base/resolve/main/pytorch_model.bin
738 MB
- Xet hash:
- eedd3b4d3d4823ce94e4d6d18bfea453b989aad4fe7ded110bcab158d2507099
- Size of remote file:
- 738 MB
- SHA256:
- 39f4a781653f5d302ad4678666b0172ccf7aefd4083e277c7a5704019f89d71a
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