Instructions to use ashraq/dv-electra-small-news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashraq/dv-electra-small-news-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ashraq/dv-electra-small-news-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ashraq/dv-electra-small-news-classification") model = AutoModelForSequenceClassification.from_pretrained("ashraq/dv-electra-small-news-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ashraq/dv-electra-small-news-classification: direct link, hf CLI and curl.
- Browser
- Download file 54 MB
-
https://huggingface.co/ashraq/dv-electra-small-news-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ashraq/dv-electra-small-news-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ashraq/dv-electra-small-news-classification/resolve/main/pytorch_model.bin
54 MB
- Xet hash:
- 37ede41aca922d2f494dc95cf7e0975207e03428695528307fedf4e8d6d137b2
- Size of remote file:
- 54 MB
- SHA256:
- 1f490f7bf3037b9afb10261d0a9765b4c67cd271b0efdf83b85630130efbfc21
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