Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use egerber1/classifier-de1_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egerber1/classifier-de1_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="egerber1/classifier-de1_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("egerber1/classifier-de1_roberta") model = AutoModelForSequenceClassification.from_pretrained("egerber1/classifier-de1_roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24568989f26cfa53459080cdffa9c97eaba73267a71927bc72f3433f72a0821b
- Size of remote file:
- 1.11 GB
- SHA256:
- 36eae5dcbca8930726afeb9366b05ba3cb6eac5016028c9bae74e7c151c906be
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