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:
- be91bdb3225b1d47a0cccb82b490881cca2355f0e4b6481310b68623610d76b2
- Size of remote file:
- 125 MB
- SHA256:
- 07b87d9e33df6268867bcdc2c0c62f785a6da2241e3d1874ab6fb528d03f8fc4
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