Text Classification
Transformers
PyTorch
English
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use dadashzadeh/cryptocurrency-intent-search-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dadashzadeh/cryptocurrency-intent-search-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dadashzadeh/cryptocurrency-intent-search-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dadashzadeh/cryptocurrency-intent-search-detection") model = AutoModelForSequenceClassification.from_pretrained("dadashzadeh/cryptocurrency-intent-search-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88a0d1626d1f5f8f909461e65a895b3f4c896f4384d5cacae03e5cda74ef0daa
- Size of remote file:
- 1.11 GB
- SHA256:
- 8b4f373c53a41c7694f6a430177a6652ccb17a25394f2930e3b2ce7ac020a9a7
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