Instructions to use RJ3vans/SignTagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJ3vans/SignTagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RJ3vans/SignTagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RJ3vans/SignTagger") model = AutoModelForTokenClassification.from_pretrained("RJ3vans/SignTagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from RJ3vans/SignTagger: direct link, hf CLI and curl.
- Browser
- Download file 1.33 GB
-
https://huggingface.co/RJ3vans/SignTagger/resolve/refs%2Fpr%2F3/model.safetensors
- Command line
-
hf download hf://RJ3vans/SignTagger@refs/pr/3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/RJ3vans/SignTagger/resolve/refs%2Fpr%2F3/model.safetensors
1.33 GB
- Xet hash:
- 1dc5beecf28c82e9729cd4550cbd9a03e782c639fb153bf2149d721183ad1fad
- Size of remote file:
- 1.33 GB
- SHA256:
- 7b148bcfdf8f017745321c88b86e033978162c8bcdfba43a1b62153856dd3b2e
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