Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use SkyR/hing-roberta-ours-run-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkyR/hing-roberta-ours-run-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SkyR/hing-roberta-ours-run-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SkyR/hing-roberta-ours-run-5") model = AutoModelForSequenceClassification.from_pretrained("SkyR/hing-roberta-ours-run-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SkyR/hing-roberta-ours-run-5: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/SkyR/hing-roberta-ours-run-5/resolve/main/tokenizer.json
- Command line
-
hf download hf://SkyR/hing-roberta-ours-run-5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SkyR/hing-roberta-ours-run-5/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 660c1982ff9928d9726ecf30f3139d5627a17c9d813a7f0f33d9eb5d20dc3b75
- Size of remote file:
- 17.1 MB
- SHA256:
- ea2094d88291c147d3775b8c94b20bc6e27ffea2acbb238df5d411712b3a4f9c
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