Instructions to use tomhaishiwo/conflicbert_binary_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomhaishiwo/conflicbert_binary_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tomhaishiwo/conflicbert_binary_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tomhaishiwo/conflicbert_binary_1") model = AutoModelForSequenceClassification.from_pretrained("tomhaishiwo/conflicbert_binary_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from tomhaishiwo/conflicbert_binary_1: direct link, hf CLI and curl.
- Browser
- Download file 241 Bytes
-
https://huggingface.co/tomhaishiwo/conflicbert_binary_1/resolve/main/README.md
- Command line
-
hf download hf://tomhaishiwo/conflicbert_binary_1/README.md
-
curl -L -o README.md https://huggingface.co/tomhaishiwo/conflicbert_binary_1/resolve/main/README.md
241 Bytes
| language: | |
| - en | |
| This is a fine-tune model based on snowood1/ConfliBERT-scr-uncased, the dataset used is 20news with 8800 training binary labeled data. | |
| Please refer to author's original paper : https://github.com/eventdata/ConfliBERT |