Instructions to use rose-e-wang/tools_a6000_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rose-e-wang/tools_a6000_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rose-e-wang/tools_a6000_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rose-e-wang/tools_a6000_2") model = AutoModelForSequenceClassification.from_pretrained("rose-e-wang/tools_a6000_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bdcd7b20236fb3c897ed7798cb537d668872455819a3af38464d869e85caff4
- Size of remote file:
- 1.42 GB
- SHA256:
- b0f2e0ef0426f558b1a24231091182f40972c9cabae0cbcbd3bc4f548aaed474
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