Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Arm627/NewsRelevanceFinetunedDistilbertBase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arm627/NewsRelevanceFinetunedDistilbertBase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arm627/NewsRelevanceFinetunedDistilbertBase")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arm627/NewsRelevanceFinetunedDistilbertBase") model = AutoModelForSequenceClassification.from_pretrained("Arm627/NewsRelevanceFinetunedDistilbertBase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Arm627/NewsRelevanceFinetunedDistilbertBase: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/Arm627/NewsRelevanceFinetunedDistilbertBase/resolve/main/training_args.bin
- Command line
-
hf download hf://Arm627/NewsRelevanceFinetunedDistilbertBase/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Arm627/NewsRelevanceFinetunedDistilbertBase/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 737c2a69ecf86a12f4e9f9d1322552dd71a698eb8005452d0d30559105acc19e
- Size of remote file:
- 3.64 kB
- SHA256:
- 0567a5af88788deb781d4f8db37b502e5d2d48dd57f6c23884678c24351e28d4
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