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:
- 66c865eb3459f7b065a1624e3162d1a3487c5c2b23005090c7249a74ac68b31d
- Size of remote file:
- 4.48 GB
- SHA256:
- 10e11e407fa86a6ab1ce02196171e5b2b4613d79c187e48ba0f0300f3b92512c
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