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
File size: 187 Bytes
022a4c4 | 1 2 3 4 5 6 7 8 9 10 | {
"vocab_size": 50101,
"embedding_dim": 768,
"mask_token": "[MASK]",
"mask_token_id": 4,
"cls_token": "[CLS]",
"cls_token_id": 1,
"sep_token": "[SEP]",
"sep_token_id": 2
} |