Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use phunganhsang/Revision_Meta_XLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phunganhsang/Revision_Meta_XLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="phunganhsang/Revision_Meta_XLM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("phunganhsang/Revision_Meta_XLM") model = AutoModelForSequenceClassification.from_pretrained("phunganhsang/Revision_Meta_XLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f76edc19c9877674430c2fa5b54d53c8068f4cb4b157e8f07bd59c1897933186
- Size of remote file:
- 17.1 MB
- SHA256:
- 22c08e6281dd0e52dc068a084ac98ef2f8802277af65f5e469e22a35be598e6a
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