Instructions to use UKP-SQuARE/tweac_16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UKP-SQuARE/tweac_16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UKP-SQuARE/tweac_16")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UKP-SQuARE/tweac_16") model = AutoModelForSequenceClassification.from_pretrained("UKP-SQuARE/tweac_16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 537949e65731494a7021c7e005e949b716555064050e3627768d7e67c5fe4eca
- Size of remote file:
- 438 MB
- SHA256:
- 2a47eb9fe62200f9a13b45f6e6a0f938c7fdefa8075452ed4219288d8a242bf5
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