Instructions to use emaeon/trained_cppbert5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emaeon/trained_cppbert5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emaeon/trained_cppbert5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emaeon/trained_cppbert5") model = AutoModelForSequenceClassification.from_pretrained("emaeon/trained_cppbert5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from emaeon/trained_cppbert5: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/emaeon/trained_cppbert5/resolve/main/model.safetensors
- Command line
-
hf download hf://emaeon/trained_cppbert5/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/emaeon/trained_cppbert5/resolve/main/model.safetensors
499 MB
- Xet hash:
- 6cb8020804ca5b178ae6a4d097c038705b3dc3fdccdda864bb88e059ef21baad
- Size of remote file:
- 499 MB
- SHA256:
- 37819d01f8d67587ae3c60db993db410e79f5b6b3c54324d27ae6f95370b864e
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