Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use asparius/bert-base-combined-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asparius/bert-base-combined-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="asparius/bert-base-combined-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("asparius/bert-base-combined-large") model = AutoModelForSequenceClassification.from_pretrained("asparius/bert-base-combined-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from asparius/bert-base-combined-large: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/asparius/bert-base-combined-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://asparius/bert-base-combined-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/asparius/bert-base-combined-large/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- df887e3244b8e40b83f84216e4f0e26315ecc6d860d9be138cd7349c742a4e31
- Size of remote file:
- 443 MB
- SHA256:
- 44e89d8ccda504b56a96c98487e154199cfb65905d13ed048a252ec989092d62
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