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 training_args.bin from jialicheng/imdb_deberta-base: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/jialicheng/imdb_deberta-base/resolve/main/training_args.bin
- Command line
-
hf download hf://jialicheng/imdb_deberta-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jialicheng/imdb_deberta-base/resolve/main/training_args.bin
3.63 kB
- Xet hash:
- 2b69d64932c14399ac78f32404229eec06c89d1044a3ffdeafc0e6642d1bcc4c
- Size of remote file:
- 3.63 kB
- SHA256:
- 0281b25f752f418d3ef28b56395ea4c47f253624c2921ce32e22c95ed1a7acf4
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