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 pred_logit_eval.npy from jialicheng/imdb_deberta-base: direct link, hf CLI and curl.
- Browser
- Download file 200 kB
-
https://huggingface.co/jialicheng/imdb_deberta-base/resolve/main/pred_logit_eval.npy
- Command line
-
hf download hf://jialicheng/imdb_deberta-base/pred_logit_eval.npy
-
curl -L -o pred_logit_eval.npy https://huggingface.co/jialicheng/imdb_deberta-base/resolve/main/pred_logit_eval.npy
200 kB
- Xet hash:
- 5bb30628ddd6d3e36a0a0ae8c390602da6ff4da41b4a7be621147566dca68386
- Size of remote file:
- 200 kB
- SHA256:
- 1e920968a87e67adc67049321999648e769ebf0914f219dc8461b8719228512a
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