Text Classification
Transformers
ONNX
Safetensors
English
Portuguese
modernbert
feature-extraction
encoder
typed-decisions
decision-index
cpu
jev
jev-alternative
decision-model
text-embeddings-inference
Instructions to use Lukitaduarte/dinah-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lukitaduarte/dinah-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lukitaduarte/dinah-0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Lukitaduarte/dinah-0") model = AutoModel.from_pretrained("Lukitaduarte/dinah-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Lukitaduarte/dinah-0: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/Lukitaduarte/dinah-0/resolve/main/tokenizer.json
- Command line
-
hf download hf://Lukitaduarte/dinah-0/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Lukitaduarte/dinah-0/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.