Instructions to use selsar/cv_profession with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/cv_profession with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/cv_profession")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/cv_profession") model = AutoModelForSequenceClassification.from_pretrained("selsar/cv_profession", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
b1ffa06 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:0c405b11c22d1def92c599a77ffa8a37b2f7d35654651510aa834cd2d54d5328
size 16316126
|