Instructions to use gplsi/Constructive_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gplsi/Constructive_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gplsi/Constructive_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gplsi/Constructive_model") model = AutoModelForSequenceClassification.from_pretrained("gplsi/Constructive_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from gplsi/Constructive_model: direct link, hf CLI and curl.
- Browser
- Download file 851 kB
-
https://huggingface.co/gplsi/Constructive_model/resolve/main/vocab.json
- Command line
-
hf download hf://gplsi/Constructive_model/vocab.json
-
curl -L -o vocab.json https://huggingface.co/gplsi/Constructive_model/resolve/main/vocab.json
851 kB
File too large to display, you can check the raw version instead.