Text Classification
Transformers
PyTorch
JAX
Safetensors
English
bert
news
classification
mini
Eval Results (legacy)
Instructions to use mrm8488/bert-mini-finetuned-age_news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-mini-finetuned-age_news-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/bert-mini-finetuned-age_news-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-mini-finetuned-age_news-classification") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/bert-mini-finetuned-age_news-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mrm8488/bert-mini-finetuned-age_news-classification: direct link, hf CLI and curl.
- Browser
- Download file 44.7 MB
-
https://huggingface.co/mrm8488/bert-mini-finetuned-age_news-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mrm8488/bert-mini-finetuned-age_news-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mrm8488/bert-mini-finetuned-age_news-classification/resolve/main/pytorch_model.bin
44.7 MB
- Xet hash:
- 93ea809dca253782de025d401971cd471987fffed7bbe6993eb63ec0479d0076
- Size of remote file:
- 44.7 MB
- SHA256:
- 1a5001bf5af86af84a07a2e7a986062643cf47297a8c632195483e3d4bde31ce
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