Text Classification
Transformers
ONNX
Safetensors
German
xlm-roberta
job-classification
german
sales-classification
taxonomy-sales
text-embeddings-inference
Instructions to use Ashybalka/xlm-roberta-taxonomy-sales-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashybalka/xlm-roberta-taxonomy-sales-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ashybalka/xlm-roberta-taxonomy-sales-de")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ashybalka/xlm-roberta-taxonomy-sales-de") model = AutoModelForSequenceClassification.from_pretrained("Ashybalka/xlm-roberta-taxonomy-sales-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5423d383c303d4b25142a782ce1f6a6e2c41c5f5ba12cccb9e4405f46d820522
- Size of remote file:
- 1.11 GB
- SHA256:
- b4be3cea70a0db636762023d0a6dfebb84f7e71b0ca62e09e38a14d32988045e
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