Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wcyat/roberta-suicide-detection-hk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wcyat/roberta-suicide-detection-hk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wcyat/roberta-suicide-detection-hk")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wcyat/roberta-suicide-detection-hk") model = AutoModelForSequenceClassification.from_pretrained("wcyat/roberta-suicide-detection-hk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wcyat/roberta-suicide-detection-hk: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/wcyat/roberta-suicide-detection-hk/resolve/main/training_args.bin
- Command line
-
hf download hf://wcyat/roberta-suicide-detection-hk/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wcyat/roberta-suicide-detection-hk/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 35c12913c3cf2c120910aff10840eae243b67b2d347acd1d8de1b8bab0e47d42
- Size of remote file:
- 4.92 kB
- SHA256:
- 07d6f88602b9f599863491ef0b94e6f1deb138dec9ea59c76af050b49e6fc9ee
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