Feature Extraction
Transformers
Safetensors
pivot
decision-making
classification
scoring
custom_code
Instructions to use Q1z/Pivot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Q1z/Pivot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Q1z/Pivot", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Q1z/Pivot", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Q1z/Pivot: direct link, hf CLI and curl.
- Browser
- Download file 4.73 MB
-
https://huggingface.co/Q1z/Pivot/resolve/main/tokenizer.json
- Command line
-
hf download hf://Q1z/Pivot/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Q1z/Pivot/resolve/main/tokenizer.json
4.73 MB
File too large to display, you can check the raw version instead.