Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
genre
text-genre
text-embeddings-inference
Instructions to use classla/xlm-roberta-base-multilingual-text-genre-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/xlm-roberta-base-multilingual-text-genre-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="classla/xlm-roberta-base-multilingual-text-genre-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("classla/xlm-roberta-base-multilingual-text-genre-classifier") model = AutoModelForSequenceClassification.from_pretrained("classla/xlm-roberta-base-multilingual-text-genre-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from classla/xlm-roberta-base-multilingual-text-genre-classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/classla/xlm-roberta-base-multilingual-text-genre-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://classla/xlm-roberta-base-multilingual-text-genre-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/classla/xlm-roberta-base-multilingual-text-genre-classifier/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 0f1d12adc8d392137ea3ab4a241fb40c4a36a5e3d89b22f808aac3fb558c090d
- Size of remote file:
- 1.11 GB
- SHA256:
- 4b63659cd075ca7159307732ee44cb6fcc4f1e2eea01b6eea8f84d01d4162bfe
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