Token Classification
Transformers
Safetensors
English
deberta-v2
frame-semantics
framenet
semantic-parsing
srl
english
Instructions to use texturejc/texture-frames-trigger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use texturejc/texture-frames-trigger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="texturejc/texture-frames-trigger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("texturejc/texture-frames-trigger") model = AutoModelForTokenClassification.from_pretrained("texturejc/texture-frames-trigger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c82424920aa443be1692b311236dc54bbbd8230585efc5972a8943ff1aee804b
- Size of remote file:
- 5.2 kB
- SHA256:
- d99ad9ede6f23bd47d75def4b8715070853c39f3049288ced5ba8a8c320138f2
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