Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use BiggieW/classification_tnews_more_imbalanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiggieW/classification_tnews_more_imbalanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BiggieW/classification_tnews_more_imbalanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BiggieW/classification_tnews_more_imbalanced") model = AutoModelForSequenceClassification.from_pretrained("BiggieW/classification_tnews_more_imbalanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BiggieW/classification_tnews_more_imbalanced: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/BiggieW/classification_tnews_more_imbalanced/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BiggieW/classification_tnews_more_imbalanced/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BiggieW/classification_tnews_more_imbalanced/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- 7110442cd0ea06882a8dc1b683f856085085a65a49e5541c8331ea163c4d1ef1
- Size of remote file:
- 409 MB
- SHA256:
- 8ba41c7f7c02c6d5b68ea636d94ad6fc79bb5da137f5936f4549c5617ac7e838
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