Token Classification
Transformers
Safetensors
English
xlm-roberta
event-detection
real-time-processing
huggingface
Instructions to use oleksiydolgykh/event-message-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oleksiydolgykh/event-message-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oleksiydolgykh/event-message-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oleksiydolgykh/event-message-detector") model = AutoModelForTokenClassification.from_pretrained("oleksiydolgykh/event-message-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from oleksiydolgykh/event-message-detector: direct link, hf CLI and curl.
- Browser
- Download file 26 Bytes
-
https://huggingface.co/oleksiydolgykh/event-message-detector/resolve/4beab5a7025b64fdf3b34db65f4a3d063b3a19da/added_tokens.json
- Command line
-
hf download hf://oleksiydolgykh/event-message-detector@4beab5a7025b64fdf3b34db65f4a3d063b3a19da/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/oleksiydolgykh/event-message-detector/resolve/4beab5a7025b64fdf3b34db65f4a3d063b3a19da/added_tokens.json
26 Bytes
| { | |
| "[MESSAGE]": 250002 | |
| } | |