Feature Extraction
Transformers
PyTorch
Vietnamese
xlm-roberta
vietnamese
contrastive-learning
sentence-embedding
natural-language-inference
low-resource
nlu
Instructions to use huynhtin/ViCLSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huynhtin/ViCLSR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="huynhtin/ViCLSR")# Load model directly from transformers import AutoTokenizer, XLMRobertaForCL tokenizer = AutoTokenizer.from_pretrained("huynhtin/ViCLSR") model = XLMRobertaForCL.from_pretrained("huynhtin/ViCLSR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0944139d2ac67eb31119d8328b5759aa1250729b0c133e188f30df1963c5f98
- Size of remote file:
- 2.24 GB
- SHA256:
- ae11c9ea17c09ba66839fab6753a34bcd7d37d0f1f4cc35d1423bb65f0b318b0
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