Instructions to use FINDA-FIT/XLM-ROBERTA_LARGE_TRUE_FP_FALSE_0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FINDA-FIT/XLM-ROBERTA_LARGE_TRUE_FP_FALSE_0.3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FINDA-FIT/XLM-ROBERTA_LARGE_TRUE_FP_FALSE_0.3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FINDA-FIT/XLM-ROBERTA_LARGE_TRUE_FP_FALSE_0.3") model = AutoModelForSequenceClassification.from_pretrained("FINDA-FIT/XLM-ROBERTA_LARGE_TRUE_FP_FALSE_0.3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e46a8ab66ea9544fac1912769f20739b2b0b72b4a2e9ecba66b7c5601666b136
- Size of remote file:
- 2.24 GB
- SHA256:
- b422c68bf2a67264d54f2ab508b3ef2652834572cab2a9391e2d4ff6152b2f11
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