Instructions to use martingrzzler/clip-word-concreteness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use martingrzzler/clip-word-concreteness with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="martingrzzler/clip-word-concreteness")# Load model directly from transformers import AutoTokenizer, CLIPForRegression tokenizer = AutoTokenizer.from_pretrained("martingrzzler/clip-word-concreteness") model = CLIPForRegression.from_pretrained("martingrzzler/clip-word-concreteness", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| datasets: | |
| - martingrzzler/conreteness_ratings | |
| language: | |
| - en | |
| metrics: | |
| - pearsonr | |
| pipeline_tag: text-classification | |
| tags: | |
| - psycholinguistic | |
| - word concreteness | |