Feature Extraction
Transformers
PyTorch
TensorFlow
JAX
Safetensors
Icelandic
xlm-roberta
MaCoCu
text-embeddings-inference
Instructions to use MaCoCu/XLMR-MaCoCu-is with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaCoCu/XLMR-MaCoCu-is with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MaCoCu/XLMR-MaCoCu-is")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("MaCoCu/XLMR-MaCoCu-is") model = AutoModelForMultimodalLM.from_pretrained("MaCoCu/XLMR-MaCoCu-is") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddb11f40e3e9e5227cd685bfa8857e40eff78e472fdbed8cb9e06e37e7a0e615
- Size of remote file:
- 2.24 GB
- SHA256:
- 2a84091fa4652b9145e3ee478dd0fc08b6a6aac2cca0e86fe216caed41c8c3d0
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