Instructions to use emaeon/trained_cppbert3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emaeon/trained_cppbert3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emaeon/trained_cppbert3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emaeon/trained_cppbert3") model = AutoModelForSequenceClassification.from_pretrained("emaeon/trained_cppbert3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from emaeon/trained_cppbert3: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/emaeon/trained_cppbert3/resolve/main/model.safetensors
- Command line
-
hf download hf://emaeon/trained_cppbert3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/emaeon/trained_cppbert3/resolve/main/model.safetensors
499 MB
- Xet hash:
- b3d7811343261a4d1b17245562916303531f6d36ce9c2855e66a7b34ebe745af
- Size of remote file:
- 499 MB
- SHA256:
- 8eaa8843538f365da702ded96c46911f478dea3ec37cc3f1250036bdc9ec3c05
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