Text Classification
Transformers
Safetensors
Ukrainian
xlm-roberta
ukrainian
stress
homograph
word-sense-disambiguation
cross-encoder
tts
text-embeddings-inference
Instructions to use aloudreader/uk-stress-crossencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloudreader/uk-stress-crossencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloudreader/uk-stress-crossencoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloudreader/uk-stress-crossencoder") model = AutoModelForSequenceClassification.from_pretrained("aloudreader/uk-stress-crossencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from aloudreader/uk-stress-crossencoder: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/aloudreader/uk-stress-crossencoder/resolve/main/tokenizer.json
- Command line
-
hf download hf://aloudreader/uk-stress-crossencoder/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/aloudreader/uk-stress-crossencoder/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- a001d9b530b6a08294605dcaff7de861d4108a3aa4d28be41e943d24312ec83f
- Size of remote file:
- 17.1 MB
- SHA256:
- 013ee4d5884a2e49945b7181b918285367b7e2ebcba843106ce22e2635bb4a8a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.