Feature Extraction
Transformers
ONNX
Basque
bert
basque
euskara
int8
int4
quantized
text-embeddings-inference
Instructions to use itzune/berteus-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itzune/berteus-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="itzune/berteus-onnx")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("itzune/berteus-onnx") model = AutoModel.from_pretrained("itzune/berteus-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96169247d05a79e681e2d73a9ebef0c7e7761bff745e4390545de4afcbe9b4b1
- Size of remote file:
- 77 MB
- SHA256:
- a2bd1a6fcc0a67c15f9480b1ca71434853dff01f0d3c60681327f50aa6470632
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