Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use marianna13/link-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marianna13/link-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marianna13/link-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marianna13/link-classification") model = AutoModelForSequenceClassification.from_pretrained("marianna13/link-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marianna13/link-classification: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/marianna13/link-classification/resolve/7d7be052d152a5b010e60dfae2e715ceff2fa8b0/training_args.bin
- Command line
-
hf download hf://marianna13/link-classification@7d7be052d152a5b010e60dfae2e715ceff2fa8b0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marianna13/link-classification/resolve/7d7be052d152a5b010e60dfae2e715ceff2fa8b0/training_args.bin
3.96 kB
- Xet hash:
- 024fd10212da143c8959f4a5f179a7658fb5b0603b74e22a2497d7ca6c5d4688
- Size of remote file:
- 3.96 kB
- SHA256:
- 0b9c759a8fa2969f00745f0d183107c757090be4dad9b5b3232d778703d3f96d
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