Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use dancrvlh/Language with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dancrvlh/Language with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dancrvlh/Language")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dancrvlh/Language") model = AutoModelForSequenceClassification.from_pretrained("dancrvlh/Language", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 486dbaf847f430d627640e604c209ccfbd80d44298bcc0583de96efc77aa9d7c
- Size of remote file:
- 568 MB
- SHA256:
- cefa4b7d6a7f05adeb1318f31927ea0f0e78d8a87ca6c977b763d88a5aa6dbd1
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