Text Classification
Transformers
Safetensors
xlm-roberta
sentiment-analysis
thai
multilingual
fine-tuned
southeast-asian
text-embeddings-inference
Instructions to use ZombitX64/MultiSent-E5-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZombitX64/MultiSent-E5-Pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZombitX64/MultiSent-E5-Pro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ZombitX64/MultiSent-E5-Pro") model = AutoModelForSequenceClassification.from_pretrained("ZombitX64/MultiSent-E5-Pro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27475935e7b8d3e2be509d2b715ef234ddf27e6b9c943b971157ad18a062d4d6
- Size of remote file:
- 18.1 MB
- SHA256:
- 4d63c638aeb3a2ce48e67df237bb49788d3dc7fbc04198d3d0831a0fae100d19
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