Instructions to use amphora/FinABSA-DeBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amphora/FinABSA-DeBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amphora/FinABSA-DeBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amphora/FinABSA-DeBERTa") model = AutoModelForSequenceClassification.from_pretrained("amphora/FinABSA-DeBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from amphora/FinABSA-DeBERTa: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/amphora/FinABSA-DeBERTa/resolve/main/tokenizer.json
- Command line
-
hf download hf://amphora/FinABSA-DeBERTa/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/amphora/FinABSA-DeBERTa/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.