Feature Extraction
Transformers
PyTorch
Safetensors
Spanish
xlm-roberta
beto
galen
text-embeddings-inference
Instructions to use IIC/XLM-R_Galen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/XLM-R_Galen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="IIC/XLM-R_Galen")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("IIC/XLM-R_Galen") model = AutoModel.from_pretrained("IIC/XLM-R_Galen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.a4d0e35
-
Add citation to README.md
Verified signaturecacc608
-
Add README.md
e0e1218 -
Upload the tokenizer
6e19492 -
Upload the model
d1c23b3 -
initial commit
331022a