Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use qandos0/SentArEng_V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qandos0/SentArEng_V0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="qandos0/SentArEng_V0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("qandos0/SentArEng_V0") model = AutoModelForSequenceClassification.from_pretrained("qandos0/SentArEng_V0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4d2e2f9230c2e787c6195edf187c680f40bcef9d674949ad461cd9296454cce
- Size of remote file:
- 17.1 MB
- SHA256:
- b0ebf3e7cfe6347b0b6b82a19702f2f60528b0653b70195c4093b3cb3bcb8cd7
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