Instructions to use research-dump/xlm_roberta_base_temp_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/xlm_roberta_base_temp_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/xlm_roberta_base_temp_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/xlm_roberta_base_temp_classifier") model = AutoModelForSequenceClassification.from_pretrained("research-dump/xlm_roberta_base_temp_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f436e9ed2a78e2e36ba9e7752e2e5d0cd40ce864c61338f71a954a60919d4541
- Size of remote file:
- 17.1 MB
- SHA256:
- 4df40ab88de1741f99292008c6cb25d0c1795b0bca8e4d4b0bc2c2f6855c57d6
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