Instructions to use summerdevlin46/XLMR-multi-en-wo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use summerdevlin46/XLMR-multi-en-wo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="summerdevlin46/XLMR-multi-en-wo")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("summerdevlin46/XLMR-multi-en-wo") model = AutoModelForTokenClassification.from_pretrained("summerdevlin46/XLMR-multi-en-wo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a60b124bd8173b64890a309a7ed346717e33227dc7e42e33834f1a3c338ec0c
- Size of remote file:
- 5.37 kB
- SHA256:
- 06930dc683f5e6f9a1d996c868756f2f48ac4912d68458c189708a2395c7c2b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.