Text Classification
Transformers
Safetensors
English
xlm-roberta
skill-detection
sentence-classification
ESCO
text-embeddings-inference
Instructions to use nurlanm/ESCOXLM-R_ENG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nurlanm/ESCOXLM-R_ENG with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nurlanm/ESCOXLM-R_ENG")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nurlanm/ESCOXLM-R_ENG") model = AutoModelForSequenceClassification.from_pretrained("nurlanm/ESCOXLM-R_ENG") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ba0aa2b4f367e00962d2a0e5e6c89ae472636fd9169d67adc876351568cff3a
- Size of remote file:
- 5.3 kB
- SHA256:
- 1124fc6417b5794aea354210b6acea4acef2ffd51a8ecf1189260ccb906088e8
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