Instructions to use j-hartmann/MindMiner-Binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use j-hartmann/MindMiner-Binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="j-hartmann/MindMiner-Binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("j-hartmann/MindMiner-Binary") model = AutoModelForSequenceClassification.from_pretrained("j-hartmann/MindMiner-Binary") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
8814b6d | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:d49369a42b9a1d99ec98d6475a0f030d7b3d30d5dd6daa52897148942c4f04a1
size 501040415
|