Instructions to use Centic-AI/kols_projects_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Centic-AI/kols_projects_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Centic-AI/kols_projects_classification_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Centic-AI/kols_projects_classification_model") model = AutoModelForSequenceClassification.from_pretrained("Centic-AI/kols_projects_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Centic-AI/kols_projects_classification_model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Centic-AI/kols_projects_classification_model/resolve/main/model.safetensors
- Command line
-
hf download hf://Centic-AI/kols_projects_classification_model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Centic-AI/kols_projects_classification_model/resolve/main/model.safetensors
438 MB
- Xet hash:
- 476fd2b99473e7cabf67698305066d6993bd9ae973a97bcd9e22805b5cc4cc32
- Size of remote file:
- 438 MB
- SHA256:
- af1fa1d26766b097c7c4863f714117f5b995d615ac005b43c1e6dd5445f603d8
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