Instructions to use lixugang/ch_text_001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lixugang/ch_text_001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lixugang/ch_text_001")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lixugang/ch_text_001") model = AutoModelForSequenceClassification.from_pretrained("lixugang/ch_text_001", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b63362b33547f104a0828962c41b061ea0952a571ba0af7c40d3048e40cbab8e
- Size of remote file:
- 4.73 kB
- SHA256:
- e265f413731753501560e6ab85bfd3382558114f8e6a5574b7dce9e7e0568044
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