Instructions to use selsar/cv_three_groups_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/cv_three_groups_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/cv_three_groups_binary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/cv_three_groups_binary") model = AutoModelForSequenceClassification.from_pretrained("selsar/cv_three_groups_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from selsar/cv_three_groups_binary: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/selsar/cv_three_groups_binary/resolve/main/model.safetensors
- Command line
-
hf download hf://selsar/cv_three_groups_binary/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/selsar/cv_three_groups_binary/resolve/main/model.safetensors
1.12 GB
- Xet hash:
- e6015c8d44f53a2c12c290952a995cbdd05f77eb0ac9f6722513cfbfbc7a738e
- Size of remote file:
- 1.12 GB
- SHA256:
- 92ac44e5fe6f931e355ed1cd0e9cf13016cf52af1ff0063218c20d2682790726
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